Raúl Vicente

The paper identifies a 127-gene core network in human astrocytes linking aging to neurodegenerative and cardiovascular diseases through proteostasis and stress signaling.

The paper identifies shared proteins and pathways between cardiovascular and cognitive diseases using protein interaction network analysis, highlighting oxidative and glycative stress mechanisms in vascular cognitive impairment.

This study uses machine learning to identify spectral signatures in human brain activity that correlate with perceptual categorization of visual stimuli.

The paper develops a biophysical model to explain how Purkinje cells learn time intervals through intra-cellular calcium signaling and feedback loops, rather than synaptic weights.

The paper introduces a method for visualizing mental state spaces to help users find effective BCI control strategies through interactive exploration.

ViraMiner uses deep learning on raw metagenomic contigs to identify viral genomes in human samples, achieving high accuracy for classification.

This study uses a recurrent neural network to decode rat location from hippocampal recordings, showing improved accuracy over a Bayesian model with flat priors.

The paper investigates the alignment between gamma band activity in the human visual cortex and feature transformations in deep convolutional neural networks (DCNNs) along the ventral visual pathway.

The paper introduces a new readout architecture for echo state networks with multiple linear readout modules controlled by a separate module, showing modest performance improvements on time series tasks.

VREX is an open-source Unity toolbox that enables researchers to create 3D virtual reality experiments for psychology and neuroscience, offering procedural room generation and experiment management.