Hasil untuk "Neurophysiology and neuropsychology"

M. Farah

Shiroshita N, Obata R, Kawana F et al.

Nanako Shiroshita,1,* Ryoko Obata,1,2,* Fusae Kawana,1 Mitsue Kato,1 Akihiro Sato,3 Sayaki Ishiwata,3 Shoichiro Yatsu,3 Hiroki Matsumoto,3,4 Jun Shitara,3 Azusa Murata,3 Megumi Shimizu,3 Takao Kato,3,4 Shoko Suda,1,3,4 Yasuhiro Tomita,3– 5 Masaru Hiki,3 Ryo Naito,3,4 Takatoshi Kasai1,3,4 1Cardiovascular Respiratory Sleep Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan; 2Philips Japan, Tokyo, Japan; 3Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan; 4Sleep and Sleep-Disordered Breathing Center, Juntendo University Hospital, Tokyo, Japan; 5Sleep Center, Toranomon Hospital, Tokyo, Japan*These authors contributed equally to this workCorrespondence: Takatoshi Kasai, Department of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan, Tel +81-3-3813-3111, Fax +81-3-5689-0627, Email kasai-t@mx6.nisiq.netPurpose: Home sleep apnea tests (HSATs) using polygraphy devices are becoming increasingly important for evaluating obstructive sleep apnea. Alice NightOne, a widely used polygraphy device, includes automatic scoring software; however, more reliable scoring results can be provided by incorporating advanced algorithmic systems like Somnolyzer. Despite this, the accuracy of automatic scoring of this polygraphy device using such applications has not been specifically investigated. Thus, in this study, we aimed to compare the respiratory event indices (REIs) obtained via automatic scoring versus manual scoring.Patients and Methods: Data of eligible patients who underwent HSAT with this polygraphy device were retrospectively analyzed using the following three methods: 1) manual scoring; 2) default automatic scoring of the analysis software; and 3) automatic scoring with the Somnolyzer system. The REIs were calculated using these three methods and expressed as mREI, aREI, and sREI, respectively. Correlations and agreements between the aREI, sREI, and mREI were assessed.Results: Data from 20 patients were analyzed. The mean mREI, aREI, and sREI were 14.7± 13.3, 13.7± 11.8, and 14.3± 13.4 events/h, respectively. A strong correlation was found between aREI and mREI (coefficient, 0.976; P< 0.01), with a mean difference between them of 1.0 and a limit of agreement of − 5.3 to 7.3. The correlation between sREI and mREI was more prominent (coefficient, 0.996; P< 0.001); their mean difference was 0.1, with a limit of agreement of − 2.1 to 2.9.Conclusion: Automatic scoring of REI using this polygraphy device showed good correlation and agreement with manual scoring. The favorable correlation and agreement were more pronounced with the Somnolyzer system.Keywords: apnea, home sleep test, hypopnea, sleep apnea, sleep study

Abdolmehdi Behroozi, Chaopeng Shen and, Daniel Kifer

Parametric differential equations of the form du/dt = f(u, x, t, p) are fundamental in science and engineering. While deep learning frameworks such as the Fourier Neural Operator (FNO) can efficiently approximate solutions, they struggle with inverse problems, sensitivity estimation (du/dp), and concept drift. We address these limitations by introducing a sensitivity-based regularization strategy, called Sensitivity-Constrained Fourier Neural Operators (SC-FNO). SC-FNO achieves high accuracy in predicting solution paths and consistently outperforms standard FNO and FNO with physics-informed regularization. It improves performance in parameter inversion tasks, scales to high-dimensional parameter spaces (tested with up to 82 parameters), and reduces both data and training requirements. These gains are achieved with a modest increase in training time (30% to 130% per epoch) and generalize across various types of differential equations and neural operators. Code and selected experiments are available at: https://github.com/AMBehroozi/SC_Neural_Operators

Laura Gwilliams, Ilina Bhaya-Grossman, Yizhen Zhang et al.

Understanding the computational algorithm that gives rise to human language is a shared endeavor among neuroscience, linguistics, and machine learning. We propose a conceptual framework for making measurable progress toward this goal by studying the subcomponents of the processing system: its underlying representations, operations, and information flow. We review evidence from neurophysiology, neuropsychology, linguistic theory, and computational modeling and suggest future directions to push the field forward in developing a precise characterization of spoken language understanding. Overall, we claim that representations of speech properties, and the operations that generate and manipulate those representations, exist within a highly parallel, highly redundant spatiotemporal regime.

Haoxing Liu, Fangzhou Shen, Haoshen Qin and et al.

With the rapid development of civil aviation and the significant improvement of people's living standards, taking an air plane has become a common and efficient way of travel. However, due to the flight characteris-tics of the aircraft and the sophistication of the fuselage structure, flight de-lays and flight accidents occur from time to time. In addition, the life risk factor brought by aircraft after an accident is also the highest among all means of transportation. In this work, a model based on back-propagation neural network was used to predict flight accidents. By collecting historical flight data, including a variety of factors such as meteorological conditions, aircraft technical condition, and pilot experience, we trained a backpropaga-tion neural network model to identify potential accident risks. In the model design, a multi-layer perceptron structure is used to optimize the network performance by adjusting the number of hidden layer nodes and the learning rate. Experimental analysis shows that the model can effectively predict flight accidents with high accuracy and reliability.

Elham Baradari and, Ozgur B Akan

Parkinson's disease (PD) is a progressive neurodegenerative disease, and it is caused by the loss of dopaminergic neurons in the basal ganglia (BG). Currently, there is no definite cure for PD, and available treatments mainly aim to alleviate its symptoms. Due to impaired neurotransmitter-based information transmission in PD, molecular communication-based approaches can be employed as potential solutions to address this issue. Molecular Communications (MC) is a bio-inspired communication method utilizing molecules for carrying information. This mode of communication stands out for developing bio-compatible nanomachines for diagnosing and treating, particularly in addressing neurodegenerative diseases like PD, due to its compatibility with biological systems. This study presents a novel treatment method that introduces an Intelligent Dopamine Rate Modulator (IDRM), which is located in the synaptic gap between the substantia nigra pars compacta (SNc) and striatum to compensate for insufficiency dopamine release in BG caused by PD. For storing dopamine in the IDRM, dopamine compound (DAC) is swallowed and crossed through the digestive system, blood circulatory system, blood-brain barrier (BBB), and brain extracellular matrix uptakes with IDRMs. Here, the DAC concentration is calculated in these regions, revealing that the required exogenous dopamine consistently reaches IDRM. Therefore, the perpetual dopamine insufficiency in BG associated with PD can be compensated. This method reduces drug side effects because dopamine is not released in other brain regions. Unlike other treatments, this approach targets the root cause of PD rather than just reducing symptoms.

Alejandro Cuetos and, Bruno Martínez-Haya, José Manuel Romero-Enrique

Discotic colloids give rise to a paradigmatic family of liquid crystals with sound applications in Materials Science. In this paper, Monte Carlo simulations are employed to characterize the low-temperature liquid crystal phase diagram and the vapour-liquid coexistence of discotic colloids interacting via a Kihara potential. Discoidal particles with thickness-diameter aspect ratios $L^*\equiv L/D$=\,0.5, 0.3, 0.2 and 0.1 are considered. For the less anisotropic particles ($L^*$$\ge$0.2), coexistence of a vapour phase with the isotropic fluid and with the columnar liquid crystal phase is observed. As the particle anisotropy increases, the vapour-liquid coexistence shifts to lower temperatures and its density range diminishes, eventually merging with coexistences involving the liquid crystal phases. The $L^*=$\,0.1 fluid displays a rich sequence of mesophases, including a nematic phase and a novel lamellar phase in which particles arrange in layers perpendicular to the nematic director.

Valeria Vasciaveo, A. Casile, A. Ferro et al.

BACKGROUND Understanding the neuronal mechanisms of learning and memory is one of the major goals in neurophysiology and neuropsychology. Disorders related to memory consolidation are often the consequences of dynamic plasticity changes, which may lead to a reduction in spine number and density, impairing neural networks. Sleep is one of the major physiological prerequisites for memory consolidation, especially during NREM sleepwhen glymphatic system clearance takes place, too. METHOD We recently validated a protocol of SF, which mimics more closely than sleep deprivation a typical impaired sleep behavior in psychiatric and neurological disorders. In this project we want to extend our previously study on the WT mouse model to unravel the mechanisms responsible for glymphatic system disruption and its correlation with memory circuitry malfunction. We will investigate which neuronal population is affected by SF by considering three regions involved in memory consolidation: hippocampus, prefrontal cortex, and the amygdala. Additionally, chronic EEG-recordings during natural sleep/wake behavior will be performed in freely behaving mice, and all temporal and spectral parameters involved in memory consolidation will be analyzed. As for glymphatic system, we will study through MRI the possible glymphatic flux alteration with Gd-DTPA as MRI tracer in the three interested regions. RESULT In addition to the proof that SF accelerates Alzheimer's Disease (AD) pathology, we observed interesting modifications of cognitive abilities in wild type (WT) mice during behavioral tests. Moreover, in both the 5xFAD mouse model for AD and the corresponding WT mice after SF, we detected an aquaporin-4 (AQP4) modulation, which is known to play a role in neurological diseases by disrupting the glymphatic system flux. Our final goal will be to understand which is the specific circuit that leads to memory impairment, and what happens to the neurons involved during SF: degeneration, excitotoxicity or astrocyte communication failure. A future study could be to test the ability to restore cognitive functions by letting the mice free to sleep one month after SF protocol. CONCLUSION Thanks to this project, we go back to the bench to find the correlation never observed before between memory circuit deficits and the possible involvement of glymphatic system during SF.

R. Domingues, L. Domingues, V. Procaci et al.

Abstract The present review article explores the neuroscience of musical perception, examining the roles of specific brain regions in decoding and interpreting music. Musical perception engages multiple cortical and subcortical areas that work in an integrated manner to process musical elements such as melody, harmony, and rhythm. The paper reviews the current knowledge about the brain circuits involved, as well as pathological conditions that result in abnormalities of musical perception. In addition, the relationship between musical perception and neurological conditions such as epilepsy and Alzheimer's disease is explored. The present review is based on findings from structural and functional neuroimaging studies, neuropsychology, neurophysiology, and clinical research, aiming to show how the brain transforms music sounds into meaningful experiences and addressing pathological conditions in which this complex process may be affected, either in isolation or in association with other forms of neurological impairment.

Jennifer Rogers and, Anamaria Crisan

Automated Machine Learning (AutoML) technology can lower barriers in data work yet still requires human intervention to be functional. However, the complex and collaborative process resulting from humans and machines trading off work makes it difficult to trace what was done, by whom (or what), and when. In this research, we construct a taxonomy of data work artifacts that captures AutoML and human processes. We present a rigorous methodology for its creation and discuss its transferability to the visual design process. We operationalize the taxonomy through the development of AutoMLTrace, a visual interactive sketch showing both the context and temporality of human-ML/AI collaboration in data work. Finally, we demonstrate the utility of our approach via a usage scenario with an enterprise software development team. Collectively, our research process and findings explore challenges and fruitful avenues for developing data visualization tools that interrogate the sociotechnical relationships in automated data work.

H. Chaggara, A. Gahami and, N. Ben Romdhane

In this paper, we derive some explicit expansion formulas associated to Brenke polynomials using operational rules based on their corresponding generating functions. The obtained coefficients are expressed either in terms of finite double sums or finite sums or sometimes in closed hypergeometric terms. The derived results are applied to Generalized Gould-Hopper polynomials and Generalized Hermite polynomials introduced by Szegö and Chihara. Some well-known duplication and convolution formulas are deduced as particular cases.

Menatalla Elwan, Ross Fowkes, David Lewis-Smith et al.

SMC1A variants are known to cause Cornelia de Lange Syndrome (CdLS) which encompasses a clinical spectrum of intellectual disability, dysmorphic features (long or thick eyebrows, a hypomorphic philtrum and small nose) and, in some cases, epilepsy. More recently, SMC1A truncating variants have been described as the cause of a neurodevelopmental disorder with early-childhood onset drug-resistant epilepsy with seizures that occur in clusters, similar to that seen in PCDH19-related epilepsy, but without the classical features of CdLS. Here, we report the case of a 28-year-old woman with a de novo heterozygous truncating variant in SMC1A who unusually presented with seizures at the late age of 12 years and had normal development into adulthood.

Prashanth S. Velayudhan, Jordan J. Mak, Lisa M. Gazdzinski et al.

Abstract Background Following one mild traumatic brain injury (mTBI), there is a window of vulnerability during which subsequent mTBIs can cause substantially exacerbated impairments. Currently, there are no known methods to monitor, shorten or mitigate this window. Methods To characterize a preclinical model of this window of vulnerability, we first gave male and female mice one or two high-depth or low-depth mTBIs separated by 1, 7, or 14 days. We assessed brain white matter integrity using silver staining within the corpus callosum and optic tracts, as well as behavioural performance on the Y-maze test and visual cliff test. Results The injuries resulted in windows of white matter vulnerability longer than 2 weeks but produced no behavioural impairments. Notably, this window duration is substantially longer than those reported in any previous preclinical vulnerability study, despite our injury model likely being milder than the ones used in those studies. We also found that sex and impact depth differentially influenced white matter integrity in different white matter regions. Conclusions These results suggest that the experimental window of vulnerability following mTBI may be longer than previously reported. Additionally, this work highlights the value of including white matter damage, sex, and replicable injury models for the study of post-mTBI vulnerability and establishes important groundwork for the investigation of potential vulnerability mechanisms, biomarkers, and therapies.

Yuqin Sun, Yuting Chen, Hudong Zhang et al.

Abstract Background Electromagnetic induction has recently been considered as an important factor affecting the activity of neurons. However, as an important form of intervention in epilepsy treatment, few people have linked the two, especially the related dynamic mechanisms have not been explained clearly. Methods Considering that electromagnetic induction has some brain area dependence, we proposed a modified two-compartment cortical thalamus model and set eight different key bifurcation parameters to study the transition mechanisms of epilepsy. We compared and analyzed the application and getting rid of memristors of single-compartment and coupled models. In particular, we plotted bifurcation diagrams to analyze the dynamic mechanisms behind abundant discharge activities, which mainly involved Hopf bifurcations (HB), fold of cycle bifurcations (LPC) and torus bifurcations (TR). Results The results show that the coupled model can trigger more discharge states due to the driving effect between compartments. Moreover, the most remarkable finding of this study is that the memristor shows two sides. On the one hand, it may reduce tonic discharges. On the other hand, it may cause new pathological states. Conclusions The work explains the control effect of memristors on different brain regions and lays a theoretical foundation for future targeted therapy. Finally, it is hoped that our findings will provide new insights into the role of electromagnetic induction in absence seizures.

Arvin Naeimi, Arash Zaminy, Naser Amini et al.

Abstract Background One of the most serious nervous system diseases is spinal cord injury(SCI), which is increasing for various reasons. Although no definitive treatment has yet been identified for SCI, one possible treatment is adipose-derived stem cells(ADSCs). However, a key issue in transplantation is improving cells’ survival and function in the target tissue. Melatonin(MT) hormone with antioxidant properties can prolong cell survival and improve cell function. This study investigates the pre-conditioning of ADSCs with melatonin for enhancing the engraftment and neurological function of rats undergoing SCI. Methods 42 male Sprague–Dawley rats were divided into six groups, including Control, Sham, Model, Vehicle, and Lesion treatments A and B. After acquiring white adipose tissue, stem cells were evaluated by flow cytometry. SCI was then applied in Model, Vehicle, A, and B groups. Group A and B received ADSCs and ADSCs + melatonin, respectively, 1 week after SCI, but the vehicle received only an intravenous injection for simulation; The other groups were recruited for the behavioral test. Immunohistochemistry(IHC) was used to assess the engraftment and differentiation of ADSCs in the SCI site. Basso, Beattie, and Bresnahan's score was used to evaluate motor function between the six groups. Results Histological studies and cell count confirmed ADSCs implantation at the injury site, which was higher in the MT-ADSCs (P < 0.001). IHC revealed the differentiation of ADSCs and MT-ADSCs into neurons, astrocytes, and oligodendrocyte lineage cells, which were higher in MT-ADSCs. Functional improvement was observed in SCI + ADSCs and SCI + MT-ADSCs groups. Conclusion The pre-conditioning of ADSCs with melatonin positively affects engraftment and neuronal differentiation in SCI but does not impact performance improvement compared to the ADSCs.

Jeanine Treffers-Daller and, Ozlem Çetinoğlu

In this paper we describe the process of collection, transcription, and annotation of recordings of spontaneous speech samples from Turkish-German bilinguals, and the compilation of a corpus called TuGeBiC. Participants in the study were adult Turkish-German bilinguals living in Germany or Turkey at the time of recording in the first half of the 1990s. The data were manually tokenised and normalised, and all proper names (names of participants and places mentioned in the conversations) were replaced with pseudonyms. Token-level automatic language identification was performed, which made it possible to establish the proportions of words from each language. The corpus is roughly balanced between both languages. We also present quantitative information about the number of code-switches, and give examples of different types of code-switching found in the data. The resulting corpus has been made freely available to the research community.

Yizhe Yang, Heyan Huang, Yang Gao et al.

The knowledge-grounded dialogue task aims to generate responses that convey information from given knowledge documents. However, it is a challenge for the current sequence-based model to acquire knowledge from complex documents and integrate it to perform correct responses without the aid of an explicit semantic structure. To address these issues, we propose a novel graph structure, Grounded Graph ($G^2$), that models the semantic structure of both dialogue and knowledge to facilitate knowledge selection and integration for knowledge-grounded dialogue generation. We also propose a Grounded Graph Aware Transformer ($G^2AT$) model that fuses multi-forms knowledge (both sequential and graphic) to enhance knowledge-grounded response generation. Our experiments results show that our proposed model outperforms the previous state-of-the-art methods with more than 10\% gains in response generation and nearly 20\% improvement in factual consistency. Further, our model reveals good generalization ability and robustness. By incorporating semantic structures as prior knowledge in deep neural networks, our model provides an effective way to aid language generation.

Anjuman Ara Khatun, Ruby Varshney and, Haider Hasan Jafri

We study transition to phase synchronization in an ensemble of Stuart-Landau oscillators interacting on a star network. We observe that by introducing frequency weighted coupling and time scale variations in the dynamics of nodes, system exhibits a first order explosive transition to phase synchrony. Further, we extend this study to understand the nature of synchronization in case of two coupled star networks. In presence of symmetry preserving (direct) coupling between the hubs of the two stars, we observe that hysteresis width first increases and then saturates for increasing inter-star coupling strength. For symmetry breaking (conjugate) coupling, the hysteresis width first increases and then decreases with increasing inter-star coupling. As we increase the inter-star coupling further, the transition gradually becomes a second order.

R R Soumya, Anuradha Sathiyaseelan

We have progressed to a phase where there is very little difference between men and women, but the reality in many countries is that women are looked down as the inferior gender and not given career opportunities to explore. They are not let into the decision-making roles at the organization even when they have an equal qualification, experience and skill. They are placed low in the hierarchy which allows them to witness the functions at the higher level of the organization but restricts them from participating in them. There are a lot of factors like cultural, socio-demographic factors and society itself that influence this disparity in the organization. These contributory factors create the glass ceiling phenomenon at the workplace, thereby generating emotional and psychological imbalances in women employees. This is a conceptual paper aiming to explore the concept and impact of mindfulness, and various concepts of mindfulness could be used as an emotional aid to treat the psychological effects of the glass ceiling. It further explains some of the mindful concepts like mindful walking, mindful life and mindfulness-based stress reduction technique in treating some of the psychological and emotional issues like depression, anxiety, frustration, traumatic experiences, adjustment issues, addiction, stress, low self-esteem, low self-confidence and aggression. It also elucidates adopting mindfulness techniques in real organizational scenarios where women are constantly discriminated because of their gender and opportunities are taken away.

Takashi Imoto, Yuya Seki, Yuichiro Matsuzaki and et al.

Quantum annealing is a promising method for solving combinational optimization problems and performing quantum chemical calculations. The main sources of errors in quantum annealing are the effects of decoherence and non-adiabatic transition. We propose a method for suppressing both these effects using inhomogeneous twist operators corresponding to the twist angles of transverse fields applied to qubits. Furthermore, we adopt variational methods to determine the optimal inhomogeneous twist operator for minimizing the energy of the state after quantum annealing. Our approach is useful for increasing the energy gap and/or making the quantum states robust against decoherence during quantum annealing. In summary, our results can pave the way to a new approach for realizing practical quantum annealing.