Advances in brain science and computer technology in the past decade have led to exciting developments in brain–computer interface (BCI), thereby making BCI a top research area in applied science. The renaissance of BCI opens new methods of neurorehabilitation for physically disabled people (e.g. paralyzed patients and amputees) and patients with brain injuries (e.g. stroke patients). Recent technological advances such as wireless recording, machine learning analysis, and real-time temporal resolution have increased interest in electroencephalographic (EEG) based BCI approaches. Many BCI studies have focused on decoding EEG signals associated with whole-body kinematics/kinetics, motor imagery, and various senses. Thus, there is a need to understand the various experimental paradigms used in EEG-based BCI systems. Moreover, given that there are many available options, it is essential to choose the most appropriate BCI application to properly manipulate a neuroprosthetic or neurorehabilitation device. The current review evaluates EEG-based BCI paradigms regarding their advantages and disadvantages from a variety of perspectives. For each paradigm, various EEG decoding algorithms and classification methods are evaluated. The applications of these paradigms with targeted patients are summarized. Finally, potential problems with EEG-based BCI systems are discussed, and possible solutions are proposed.

Recognition of a specific visual target among equally familiar distracters requires neural mechanisms for tracking items in working memory. Event-related functional magnetic resonance imaging revealed evidence for two such mechanisms: (i) Enhanced neural responses, primarily in the frontal cortex, were associated with the target and were maintained across repetitions of the target. (ii) Reduced responses, primarily in the extrastriate visual cortex, were associated with stimulus repetition, regardless of whether the stimulus was a target or a distracter. These complementary neural mechanisms track the status of familiar items in working memory, allowing for the efficient recognition of a currently relevant object and rejection of irrelevant distracters.