BCI technology enables communication, which does not rely on neuromuscular control thereby offering assistance to those who require alternative communicatory and control mechanisms because of neuromuscular deficiencies due to disease or spinal/brain damage. BCI have advanced significantly in the past few years but there remain a significant number of problems and issues to be resolved due to the high level of noise, and the non-stationary nature of the neural signals used in BCI. In addition to many signal processing related topics and application development associated with field of BCIs we also encourage submissions in the following additional areas of interest: Computational models of brain circuitry in normal and pathological conditions Mathematical and neurocomputational models are contributing to the understanding of structural, functional, and behavioural aspects of brain regions. They can play an instrumental role in bridging the gap between the brain and behavior and help to unravel the underlying mechanisms of therapy. It is desirable that a computational model be a supplement to behavioural and experimental neuroscientists in understanding functional anomalies in the brain corresponding to certain medical conditions but also in how models can be exploited to develop BCI signal processing strategies and understand neuroadaptation during BCI training and usage. Cognitive robotics Controlling robots for assistive devices and industrial applications is a key area of Computational Intelligence research. It is critical to consider the intentional action-perception cycle, when the robot develops its own understanding of the world through interactions and hypothesis testing. Brain inspired approaches to robotic control and cognitive robotics have become increasingly popular with various breakthroughs in the field of autonomous systems designs and implementations. We are keen to receive submissions on interfacing the brain with robotic assistive devices and neuroprostheses.