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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...

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 ...

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...

Abstract Pattern separation, the ability of a network to distinguish similar inputs by transforming them into distinct outputs, was postulated by the Marr-Albus theory to be realized by divergent feedforward excitatory c...

IntroductionHuman space exploration is progressing into an unprecedented era characterized by extended-duration missions, the establishment of permanent lunar bases, and planned crewed voyages to Mars. These activities i...

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...

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...

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...

Abstract Cognitive deficits are a hallmark of Alzheimer’s disease (AD), and effective treatments remain elusive. Transcranial alternating current stimulation (tACS), a non-invasive technique, has shown potential in imp...

Abstract At dawn, we experience a shift from slumber to sentience following neurophysiological transitions, termed as sleep inertia (SI). Although resting-state fMRI studies have discovered brain reorganizations during S...

(Versión disponible en RI ITBA: preprint en arXiv). Versión final publicada disponible via DOI. "Large-scale neural mass models have been widely used to simulate resting-state brain activity from structural connectiv...

"We investigate the role of connection density in an adaptive network model of chaotic units that dynamically rewire based on their internal states and local coherence. By systematically varying the network's connectivit...