dynamic neural field

Atmospheric temperature is fundamental information for various industries, such as production, life, and scientific research. The temperature error induced by the solar rays can reach 1 °C or even higher. A hemispherical shell-shaped atmospheric temperature measuring instrument that can reduce heat pollution and increase air velocity was designed. First, the instrument was optimized using computational fluid dynamics (CFD) software packages. Then, the CFD software packages were employed to quantify the temperature errors of the instrument with varying situations...

INTRODUCTION: Service robot technology is increasingly gaining prominence in the field of artificial intelligence. However, persistent limitations continue to impede its widespread implementation. In this regard, human motion pose estimation emerges as a crucial challenge necessary for enhancing the perceptual and decision-making capacities of service robots. METHOD: This paper introduces a groundbreaking model, YOLOv8-ApexNet, which integrates advanced technologies, including Bidirectional Routing Attention (BRA) and Generalized Feature Pyramid Network (GFPN)...

Semi-supervised learning has made significant progress in medical image segmentation. However, existing methods primarily utilize information from a single dimensionality, resulting in sub-optimal performance on challenging magnetic resonance imaging (MRI) data with multiple segmentation objects and anisotropic resolution. To address this issue, we present a Hybrid Dual Mean-Teacher (HD-Teacher) model with hybrid, semi-supervised, and multi-task learning to achieve effective semi-supervised segmentation. HD-Teacher employs a 2D and a 3D mean-teacher network to produce segmentation labels and signed distance fields from the hybrid information captured in both dimensionalities...

In modern wireless communication systems, the scarcity of spectrum resources poses challenges to the performance and efficiency of the system. Spectrum prediction technology can help systems better plan and schedule resources to respond to the dynamic changes in spectrum. Dynamic change in the spectrum refers to the changes in the radio spectrum in a wireless communication system. It means that the available spectrum resources may change at different times and locations. In response to this current situation, this study first constructs a communication collaborative spectrum sensing model using channel aliasing dense connection networks...

In recent years, the global e-commerce landscape has witnessed rapid growth, with sales reaching a new peak in the past year and expected to rise further in the coming years. Amid this e-commerce boom, accurately predicting user purchase behavior has become crucial for commercial success. We introduce a novel framework integrating three innovative approaches to enhance the prediction model's effectiveness. First, we integrate an event-based timestamp encoding within a time-series attention model, effectively capturing the dynamic and temporal aspects of user behavior...

According to experts in neurology, brain tumours pose a serious risk to human health. The clinical identification and treatment of brain tumours rely heavily on accurate segmentation. The varied sizes, forms, and locations of brain tumours make accurate automated segmentation a formidable obstacle in the field of neuroscience. U-Net, with its computational intelligence and concise design, has lately been the go-to model for fixing medical picture segmentation issues. Problems with restricted local receptive fields, lost spatial information, and inadequate contextual information are still plaguing artificial intelligence...

The striatum plays a crucial role in studying epilepsy, as it is involved in seizure generation and modulation of brain activity. To explore the complex interplay between the striatum and epilepsy, we engineered advanced microelectrode arrays (MEAs) specifically designed for precise monitoring of striatal electrophysiological activities in rats. These observations were made during and following seizure induction, particularly three and 7 days post-initial modeling. The modification of graphene oxide (GO)/poly (3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS)/platinu-m nanoparticles (PtNPs) demonstrated a marked reduction in impedance (10...

Studying deception is vital for understanding decision-making and social dynamics. Recent EEG research has deepened insights into the brain mechanisms behind deception. Standard methods in this field often rely on memory, are vulnerable to countermeasures, yield false positives, and lack real-world relevance. Here, we present a comprehensive dataset from an EEG-monitored competitive, two-player card game designed to elicit authentic deception behavior. Our extensive dataset contains EEG data from 12 pairs (N = 24 participants with role switching), controlled for age, gender, and risk-taking, with detailed labels and annotations...

According to the predictive processing framework, perception emerges from the reciprocal exchange of predictions and prediction errors (PE) between hierarchically organized neural circuits. The nonlemniscal division of the inferior colliculus (IC) is the earliest source of auditory PE signals, but their neuronal generators, properties and functional relevance have remained mostly undefined. We recorded single-unit mismatch responses to auditory oddball stimulation at different intensities, together with activity evoked by two sequences of alternating tones to control frequency-specific effects...

The lateral intraparietal area (LIP) plays a crucial role in target selection and attention in primates, but the laminar microcircuitry of this region is largely unknown. To address this, we used ultra-high density laminar electrophysiology with Neuropixels probes to record neural activity in the posterior parietal cortex (PPC) of two adult marmosets while they performed a simple visual target selection task. Our results reveal neural correlates of visual target selection in the marmoset, similar to those observed in macaques and humans, with distinct timing and profiles of activity across cell types and cortical layers...

Trace eyeblink conditioning (TEBC) has been widely used to study associative learning in both animals and humans. In this paradigm, conditioned responses (CRs) to conditioned stimuli (CS) serve as a measure for retrieving learned associations between the CS and the unconditioned stimuli (US) within a trial. Memory consolidation i.e. learning over time, can be quantified as an increase in the proportion of CRs across training sessions. However, how hippocampal oscillations differentiate between successful memory retrieval within a session and consolidation across TEBC training sessions remains unknown...

Intraoperative imaging techniques for reconstructing deformable tissues in vivo are pivotal for advanced surgical systems. Existing methods either compromise on rendering quality or are excessively computationally intensive, often demanding dozens of hours to perform, which significantly hinders their practical application. In this paper, we introduce Fast Orthogonal Plane (Forplane), a novel, efficient framework based on neural radiance fields (NeRF) for the reconstruction of deformable tissues. We conceptualize surgical procedures as 4D volumes, and break them down into static and dynamic fields comprised of orthogonal neural planes...

Phase-entrainment of cells by theta oscillations is thought to globally coordinate the activity of cell assemblies across different structures, such as the hippocampus and neocortex. This coordination is likely required for optimal processing of sensory input during recognition and decision-making processes. In quadruple-area ensemble recordings from male rats engaged in a multisensory discrimination task, we investigated phase-entrainment of cells by theta oscillations in areas along the cortico-hippocampal hierarchy: somatosensory barrel (S1BF), secondary visual cortex (V2L), perirhinal cortex (PER) and dorsal hippocampus (dHC)...

The standard consolidation theory states that short-term memories located in the hippocampus enable the consolidation of long-term memories in the neocortex. In other words, the neocortex slowly learns long-term memories with a transient support of the hippocampus that quickly learns unstable memories. However, it is not clear yet what could be the neurobiological mechanisms underlying these differences in learning rates and memory time-scales. Here, we propose a novel modelling approach of the standard consolidation theory, that focuses on its potential neurobiological mechanisms...

BACKGROUND: Multi-echo chemical-shift-encoded magnetic resonance imaging (MRI) has been widely used for fat quantification and fat suppression in clinical liver examinations. Clinical liver water-fat imaging typically requires breath-hold acquisitions, with the free-breathing acquisition method being more desirable for patient comfort. However, the acquisition for free-breathing imaging could take up to several minutes. The purpose of this study is to accelerate four-dimensional free-breathing whole-liver water-fat MRI by jointly using high-dimensional deep dictionary learning and model-guided (MG) reconstruction...

Intracellular calcium plays a pivotal role in central nervous system (CNS) development by regulating various processes such as cell proliferation, migration, differentiation, and maturation. However, understanding the involvement of calcium (Ca2+ ) in these processes during CNS development is challenging due to the dynamic nature of this cation and the evolving cell populations during development. While Ca2+ transient patterns have been observed in specific cell processes and molecules responsible for Ca2+ homeostasis have been identified in excitable and non-excitable cells, further research into Ca2+ dynamics and the underlying mechanisms in neural stem cells (NSCs) is required...

Aboveground biomass (AGB) is an important indicator of the grassland ecosystem. It can be used to evaluate the grassland productivity and carbon stock. Satellite remote sensing technology is useful for monitoring the dynamic changes in AGB across a wide range of grasslands. However, due to the scale mismatch between satellite observations and ground surveys, significant uncertainties and biases exist in mapping grassland AGB from satellite data. This is also a common problem in low- and medium-resolution satellite remote sensing modeling that has not been effectively solved...

In the field of neuroscience, brain-computer interfaces (BCIs) are used to connect the human brain with external devices, providing insights into the neural mechanisms underlying cognitive processes, including aesthetic perception. Non-invasive BCIs, such as EEG and fNIRS, are critical for studying central nervous system activity and understanding how individuals with cognitive deficits process and respond to aesthetic stimuli. This study assessed twenty participants who were divided into control and impaired aging (AI) groups based on MMSE scores...

Convolutional neural networks (CNNs) have significantly advanced various fields; however, their computational demands and power consumption have escalated, posing challenges for deployment in low-power scenarios. To address this issue and facilitate the application of CNNs in power constrained environments, the development of dedicated CNN accelerators is crucial. Prior research has predominantly concentrated on developing low precision CNN accelerators using code generated from high-level synthesis (HLS) tools...

In the field of intelligent connected vehicles, the precise and real-time identification of speed bumps is critically important for the safety of autonomous driving. To address the issue that existing visual perception algorithms struggle to simultaneously maintain identification accuracy and real-time performance amidst image distortion and complex environmental conditions, this study proposes an enhanced lightweight neural network framework, YOLOv5-FPNet. This framework strengthens perception capabilities in two key phases: feature extraction and loss constraint...