Thrombotic events (TEs) occur in up to 40% of patients with vacuoles, E1 enzyme, X-linked, autoinflammatory, and somatic (VEXAS) syndrome, but data on its clinical-genomics features and anticoagulation strategies are limited. To gain more insight into this, we conducted a two-step study evaluating the prevalence and outcome of TE in VEXAS. First, among 1086 patients followed for TEs, 198 were men aged >40 years with unprovoked thrombosis and no known thrombophilia; 21 also had at least one...

Recurrent neural networks are studied along two largely parallel tracks: as machine-learning models evaluated by task performance and as computational-neuroscience models of cortical circuits evaluated by dynamical realism. Reservoir computing offers a meeting point, yet the link between dynamical regime and computational performance has not been systematically mapped in biologically constrained spiking architectures. We treat the Brunel balanced excitatory-inhibitory network as a reservoir and...

Recent advancements in neural decoding have shown promising results in reconstructing visual experiences from brain activity. However, existing approaches focus primarily on decoding within a single dataset or subject, which limits generalization across various sources of neuroimaging. In this work, we propose a novel framework for the decoding of visual stimuli between subjects and between data sets, integrating neural recordings from multiple publicly available fMRI datasets. To address...

Characterizing the information content of intracortical signals during visual processing is a central challenge in systems neuroscience. We address the problem of decoding visual information from high-density intracortical recordings in primates, using the THINGS Ventral Stream Spiking Dataset. We systematically evaluate the effects of model architecture, training objectives, and data scaling on decoding performance. Results show that decoding accuracy is jointly driven by non-linearity and...

Implantable and wearable devices require antennas that are both miniaturized and efficient, yet conventional designs are constrained by narrow bandwidth and orientation sensitivity. We report overtone ultrawideband magnetoelectric (OUWB-ME) antennas that exploit higher-order acoustic modes in polished silicon substrates to achieve a 22.6-gigahertz -10-decibel bandwidth and overtone capability in the 3- to 4-gigahertz range. Packaged into "μBots," these magnetoelectric heterostructures bonded...