Related papers: Functional Magnetic Resonance Spectroscopy in the …
Quantitative magnetic resonance imaging (qMRI) is concerned with estimating (in physical units) values of magnetic and tissue parameters e.g., relaxation times $T_1$, $T_2$, or proton density $\rho$. Recently in [Ma et al., Nature, 2013],…
What can representational similarity matrices (RSMs) tell us about a neural code? As the popularity of these summary statistics grows, so too does the need for a more complete characterization of their properties. Here, we show that…
Predicting behavioral variables from neuroimaging modalities such as magnetic resonance imaging (MRI) has the potential to allow the development of neuroimaging biomarkers of mental and neurological disorders. A crucial processing step to…
Functional connectomes capture brain interactions via synchronized fluctuations in the functional magnetic resonance imaging signal. If measured during rest, they map the intrinsic functional architecture of the brain. With task-driven…
Resting-state functional Magnetic Resonance Imaging (fMRI) is a powerful imaging technique for studying functional development of the brain in utero. However, unpredictable and excessive movement of fetuses have limited its clinical…
Conventional electromyography (EMG) measures the continuous neural activity during muscle contraction, but lacks explicit quantification of the actual contraction. Mechanomyography (MMG) and accelerometers only measure body surface motion,…
We demonstrate a technique of broadband spin torque ferromagnetic resonance (ST-FMR) with magnetic field modulation for measurements of spin wave properties in magnetic nanostructures. This technique gives great improvement in sensitivity…
Accurate diagnosis of psychiatric disorders plays a critical role in improving the quality of life for patients and potentially supports the development of new treatments. Many studies have been conducted on machine learning techniques that…
Functional magnetic resonance imaging (fMRI) plays a crucial role in neuroimaging, enabling the exploration of brain activity through complex-valued signals. These signals, composed of magnitude and phase, offer a rich source of information…
Magnetic Resonance Imaging (MRI) is a widely applied non-invasive imaging modality based on non-ionizing radiation which gives excellent images and soft tissue contrast of living tissues. We consider the modified Bloch problem as a model of…
Multiple sclerosis (MS) is a chronic inflammatory and degenerative disease of the central nervous system, characterized by the appearance of focal lesions in the white and gray matter that topographically correlate with an individual…
Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used to visualize brain activation regions by detecting hemodynamic responses associated with increased metabolic demand. While alternative MRI…
Ferromagnetic resonance (FMR) is used to study magnetic anisotropy of GaMnAs in a series of Ga$_{1 - x}$Mn$_{x}$As/Ga$_{1 - y}$Al$_{y}$As heterostructures modulation-doped by Be. The FMR experiments provide a direct measure of cubic and…
The possibility of simulating in detail in-vivo experiments could be highly beneficial to the neuroscientific community. It could easily allow for preliminary testing of different experimental conditions without having to be constrained by…
Magnetic resonance imaging (MRI) is the cornerstone technique for diagnostic medicine, biology, and neuroscience. This imaging method is highly innovative, noninvasive and its impact continues to grow. It can be used for measuring changes…
Multiple sclerosis is a chronic autoimmune disease that affects the central nervous system. Understanding multiple sclerosis progression and identifying the implicated brain structures is crucial for personalized treatment decisions.…
In recent years there has been explosive growth in the number of neuroimaging studies performed using functional Magnetic Resonance Imaging (fMRI). The field that has grown around the acquisition and analysis of fMRI data is intrinsically…
The impact of in-scanner motion on functional magnetic resonance imaging (fMRI) data has a notorious reputation in the neuroimaging community. State-ofthe-art guidelines advise to scrub out excessively corrupted frames as assessed by a…
Understanding how the brain encodes visual information is a central challenge in neuroscience and machine learning. A promising approach is to reconstruct visual stimuli, essentially images, from functional Magnetic Resonance Imaging (fMRI)…
Detecting shared neural activity from functional magnetic resonance imaging (fMRI) across individuals exposed to the same stimulus can reveal synchronous brain responses, functional roles of regions, and potential clinical biomarkers.…