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Background The heterogeneity of depression limits the treatment outcomes of intermittent theta burst stimulation (iTBS) and hinders the identification of predictive factors. This study investigated functional network con...

Biological neural network functionality depends on the vast number of connections between nodes, which can be challenging to implement artificially. One radical solution is to replace physical wiring with broadcasting of...

Abstract Traditional bridge structural condition assessments struggle to integrate the physical topological information of BIM models with the spatiotemporal evolution of long-term monitoring data, resulting in low asses...

A high efficiency hardware integration of neural networks benefits from realizing nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems have recently implemented some or all of t...

Abstract Background Aberrant functional connectivity (FC) between the left dorsolateral prefrontal cortex (DLPFC) and subgenual anterior cingulate cortex (sgACC) is a replicated neural correlate of major depressive disor...

Background Walking impairments post-stroke are common but studying their neural basis with fMRI is difficult due to motion constraints. This study used post-task resting-state residual activity (PTRRA) to investigate wal...

BackgroundThe hypothesis of decreased neural inhibition in dementia has been sparsely studied in functional magnetic resonance imaging (fMRI) data across patients with different dementia subtypes, and the role of social ...

People learn from experience, but with considerable individual differences in the degree and type of behavioral adjustments resulting from a given experience. Error driven learning rules provide an elegant framework for ...

Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, ...

Background The neuroimaging mechanism of major depressive episodes with mixed features (MMF) is not clear.Aims This study aimed to investigate the functional connectivity of the default mode network (DMN) subsystems amon...

IntroductionMusic-induced analgesia (MIA) has significant clinical value for patients with fibromyalgia (FM) and serves as a key model for understanding the complex neural mechanisms underlying the effects of music on ph...

Abstract Echo State Networks are recurrent neural networks that leverage a random reservoir’s dynamics, training only a simple readout layer. This approach is computationally efficient but limits network performance. B...

Abstract Background Subcortical structures are pivotal for cortico-subcortical communication, yet are highly vulnerable to stroke. Damage to these structures can produce widespread cortical dysfunction, but how subcortic...

Graph-based text classification has become an effective paradigm for modeling corpus-level structure, particularly under limited supervision. However, most existing approaches rely on document–word representations...

ObjectiveTo develop an accurate and efficient binary classification model for predicting the binding capacity of endocrine-disrupting chemicals （EDCs） to the G protein-coupled estrogen receptor （GPER）.MethodsGPER...

Abstract Advances in AI have transformed the traditional Internet of Things (IoT) into smarter, more versatile next-generation devices. Enhanced connectivity among sensors, actuators, and appliances boosts data availabil...

Multiport interferometers based on integrated beamsplitter meshes have recently captured interest as a platform for many emerging technologies. In this paper, we present a novel architecture for multiport interferometers...

Manipulating and real-time monitoring of neuronal activities with cell-type specificity and precise spatiotemporal resolution during animal behavior are fundamental technologies for exploring the functional connectivity,...

Reading fluency depends on rapid integration of print and speech, yet the spatiotemporal mechanisms supporting this integration in school aged children remain poorly understood. This study combined fMRI and EEG to examin...

Background Frontal lobe injury (FLI) is related to cognitive control impairments, but the influences of FLI on the internal subprocesses of cognitive control remain unclear.Aims We sought to identify specific biomarkers ...

The incidence of metabolic disorders including obesity, type 2 diabetes and metabolic syndrome have seriously increased in the last decades. These diseases - with growing impact in modern societies - constitute major ris...

In the last decades there have been significant advances in our understanding of the cellular and subcellular mechanisms underlying changes in synaptic connectivity that subserve memory formation. The so called Theory of...

In patients with brain injury, conventional clinical paradigm based on macro imaging and behavioral scales fails to achieve precise localization and dynamic assessment of neural functions and network connectivity. It is ...