Brain–computer interfaces (BCIs) employ neurophysiological signals derived from the brain to control computers or external devices. By enhancing replacing human peripheral functioning capacity, BCIs offer supplementary degrees of freedom, significantly improving individuals’ quality life, particularly offering hope for those with locked-in syndrome (LIS). Moreover, BCI applications have expande...

Many studies over the past two decades have shown that people can use brain signals to convey their intent to a computer through brain-computer interfaces (BCIs). These devices operate by recording signals from the brain and translating these signals into device commands. They can be used by people who are severely paralyzed to communicate without any use of muscle activity. One of the major im...

The intravoxel incoherent motion (IVIM) model allows to map diffusion (D) and perfusion-related parameters (F D*). Parameter estimation is, however, error-prone due the non-linearity of signal model, limited signal-to-noise ratio (SNR) small volume fraction perfusion in in-vivo brain. In present work, performance Bayesian inference was examined presence brain pathologies characterized by hypo- ...

Electroencephalograph (EEG) has been widely applied for brain-computer interface (BCI) which enables paralyzed people to directly communicate with and control external devices, due its portability, high temporal resolution, ease of use low cost. Of various EEG paradigms, steady-state visual evoked potential (SSVEP)-based BCI system uses multiple stimuli (such as LEDs or boxes on a computer scre...

Recent advancements in machine learning and deep models find them helpful designing effective complex measurement systems. At the same time, examining brain’s activities using Electroencephalography (EEG) is essential to determine mental state or thought of a person. It several application areas, such as Brain-Computer Interface (BCI), emotion recognition, disease diagnosis. The proper brain si...

Accurate measurements of longitudinal relaxation time constants (T1) in solid-state nuclear magnetic resonance (SSNMR) experiments are important for the study molecular-level structure and dynamics. Such often made under magic-angle spinning conditions; however, there numerous instances where they must be on stationary samples, which give rise to broad powder patterns arising from large anisotr...

Fractal dimension of the electroencephalographic (EEG) signal has been argued to reflect the complexity of the underlying brain processes. To this date, conventional studies of EEG in mood disorders have not been able to distinguish between patients and normal individuals. Here we show that, compared to normal subjects, EEG fractal dimension is significantly augmented in the manic episode of bi...

Fractal dimension of the electroencephalographic (EEG) signal has been argued to reflect the complexity of the underlying brain processes. To this date, conventional studies of EEG in mood disorders have not been able to distinguish between patients and normal individuals. Here we show that, compared to normal subjects, EEG fractal dimension is significantly augmented in the manic episode of bi...