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We demonstrate an application of spherical harmonic decomposition to analysis of the human electroencephalogram (EEG). We implement two methods and discuss issues specific to analysis of hemispherical, irregularly sampled data. Performance…

There is a growing effort in creating chiral transport of sound waves. However, most approaches so far are confined to the macroscopic scale. Here, we propose a new approach suitable to the nanoscale which is based on pseudomagnetic fields.…

This paper presents a novel graph convolutional neural network (GCNN)-based approach for improving the diagnosis of neurological diseases using scalp-electroencephalograms (EEGs). Although EEG is one of the main tests used for…

Simulations and experimental works have been carried out in a complementary way to engineer a basic material target mimicking the same dielectric properties of the human body. It includes a resistor in parallel with a capacitor, whose…

In this article, we explore the potential of using latent diffusion models, a family of powerful generative models, for the task of reconstructing naturalistic music from electroencephalogram (EEG) recordings. Unlike simpler music with…

In this manuscript, an effort is made in this review to address different state-of-the-art artificial tissue emulating (ATE) materials and phantom types for various operating frequencies, and fabrication procedures in order to have a better…

Electroencephalography (EEG) allows monitoring of brain activity, providing insights into the functional dynamics of various brain regions and their roles in cognitive processes. EEG is a cornerstone in sleep research, serving as the…

The creation of wave-dynamic illusion functionality is of great interests to various scientific communities, which can potentially transform an actual perception into the pre-controlled perception, thus empowering unprecedented applications…

Electrophysiological brain signals, such as electroencephalography (EEG), exhibit both periodic and aperiodic components, with the latter often modeled as 1/f noise and considered critical to cognitive and neurological processes. Although…

It is well known that Electroencephalography(EEG) and the respective evoked potentials have deep implications corresponding to specific cognitive tasks and in the diagnosis of several diseases such as epilepsy and schizophrenia. Some recent…

Brain-computer interfaces (BCIs) provide potential for applications ranging from medical rehabilitation to cognitive state assessment by establishing direct communication pathways between the brain and external devices via…

The significant inter-subject variability in electroen-cephalogram (EEG) signals often results in substantial changes to neural network weights as data distributions shift. This variability frequently causes catastrophic forgetting in…

Colloidal particles dispersed in liquid crystals can form new materials with tunable elastic and electro-optic properties. In a periodic `blue phase' host, particles should template into colloidal crystals with potential uses in photonics,…

Electroencephalography provides a non-invasive window into brain activity, offering valuable insights for neurological research, brain-computer interfaces, and clinical diagnostics. However, the development of robust machine learning models…

Background: For newborn infants in critical care, continuous monitoring of brain function can help identify infants at-risk of brain injury. Quantitative features allow a consistent and reproducible approach to EEG analysis, but only when…

I review the advancements of atomic scale nanoelectronics towards quantum neuromorphics. First, I summarize the key properties of elementary combinations of few neurons, namely long-- and short--term plasticity, spike-timing dependent…

This paper discusses the use of the scalp electric field to decode EEG-recorded brain processes. Instead of using bipolar measurements, the scalp electric field is described as a 3-vector field whose orthogonal components are obtained from…

Electroencephalogram (EEG) has shown a useful approach to produce a brain-computer interface (BCI). One-dimensional (1-D) EEG signal is yet easily disturbed by certain artifacts (a.k.a. noise) due to the high temporal resolution. Thus, it…

Given rising numbers of bilateral cochlear implant (CI) users, predominantly children, there is a clinical need for efficient and reliable tests that can objectively evaluate binaural hearing. These tests are crucial for guiding the setup…

Electroencephalography (EEG) has wide-ranging applications, from clinical diagnosis to brain-computer interfaces (BCIs). With the increasing volume and variety of EEG data, there has been growing interest in establishing foundation models…