BACKGROUND: Motion-onset visual evoked potentials (mVEP) can provide a softer stimulus with reduced fatigue, and it has potential applications for brain computer interface(BCI)systems. However, the mVEP waveform is seriously masked in the strong back...
BACKGROUND: Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (...
BACKGROUND: Neuroevolution comprises the use of evolutionary computation to define the architecture and/or to train artificial neural networks (ANNs). This strategy has been employed to investigate the behavior of rats in the elevated plus-maze, whic...
BACKGROUND: Unsupervised identification of action potentials in multi-channel extracellular recordings, in particular from high-density microelectrode arrays with thousands of sensors, is an unresolved problem. While independent component analysis (I...
BACKGROUND: Generative models of neuroimaging data, such as dynamic causal models (DCMs), are commonly used for inferring effective connectivity from individual subject data. Recently introduced "generative embedding" approaches have used DCM-based c...
BACKGROUND: Brain MRI holds promise to gauge different aspects of Parkinson's disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data.
BACKGROUND: Electroencephalogram (EEG) and electromyogram (EMG) recordings are often used in rodents to study sleep architecture and sleep-associated neural activity. These recordings must be scored to designate what sleep/wake state the animal is in...
BACKGROUND: Machine learning models have been successfully applied to neuroimaging data to make predictions about behavioral and cognitive states of interest. While these multivariate methods have greatly advanced the field of neuroimaging, their app...
BACKGROUND: Rapid eye movements (REMs) are a defining feature of REM sleep. The number of discrete REMs over time, or REM density, has been investigated as a marker of clinical psychopathology and memory consolidation. However, human detection of REM...