Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist).

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Continuous decoding of motor attempt and motor imagery from EEG activity in spinal cord injury patients.

Spinal cord injury (SCI) associates brain reorganization with a loss of cortical representation of paralyzed limbs. This effect is more pronounced in the chronic state, which can be reached approximately 6 months after the lesion. As many of the brain-computer interfaces (BCI) developed to date rely on the user motor activity, loss of this activity hinders the application of BCI technology for rehabilitation or motor compensation in these patients. This work is a preliminary study with three quadriplegic patients close to reaching the chronic state, addressing two questions: (i) whether it is still possible to use BCI technology to detect motor intention of the paralyzed hand at this state of chronicity; and (ii) whether it is better for the BCI decoding to rely on the motor attempt or the motor imagery of the hand as mental paradigm. The results show that one of the three patients had already lost the motor programs related to the hand, so it was not possible to build a motor-related BCI for him. For the other patients it was suitable to design a BCI based on both paradigms, but the results were better using motor attempt as it has broader activation associated patterns that are easier to recognize.

A telepresence mobile robot controlled with a noninvasive brain-computer interface.

This paper reports an electroencephalogram-based brain-actuated telepresence system to provide a user with presence in remote environments through a mobile robot, with access to the Internet. This system relies on a P300-based brain-computer interface (BCI) and a mobile robot with autonomous navigation and camera orientation capabilities. The shared-control strategy is built by the BCI decoding of task-related orders (selection of visible target destinations or exploration areas), which can be autonomously executed by the robot. The system was evaluated using five healthy participants in two consecutive steps: 1) screening and training of participants and 2) preestablished navigation and visual exploration telepresence tasks. On the basis of the results, the following evaluation studies are reported: 1) technical evaluation of the device and its main functionalities and 2) the users' behavior study. The overall result was that all participants were able to complete the designed tasks, reporting no failures, which shows the robustness of the system and its feasibility to solve tasks in real settings where joint navigation and visual exploration were needed. Furthermore, the participants showed great adaptation to the telepresence system.

Upper alpha neurofeedback training over the motor cortex increases SMR desynchronization in motor tasks.

Desynchronization of sensorimotor rhythms (SMR) is a distinctive feature that provides a discriminative pattern for BCI operation. However, individuals such as BCI illiterates can not produce these discriminable patterns with sufficient reliability. Additionally, SMR desynchronization can become deteriorated or extinct in patients with spinal cord injury or a cerebrovascular accident. In all these situations BCI usage is compromised. This paper proposes an intervention based on neurofeedback training of the upper alpha band to improve SMR desynchronization. The feasibility of this intervention is demonstrated in a preliminary study in which five healthy subjects were trained to increase their upper alpha band power. Such increases produced higher SMR desynchronization and better discrimination between rest and execution states of a motor task.

EEG-based upper alpha neurofeedback training improves working memory performance.

Neurofeedback (NF) training has revealed its therapeutical effects to treat a variety of neurological and psychological disorders, and has demonstrated its feasibility to improve certain cognitive aptitudes in healthy users. Although promising results of NF training exist in recent literature, the reliability of its effects remains questioned due to a lack of deep studies examining its impact on the human electrophysiology. This paper presents a NF training aimed at improving working memory performance in healthy users by the enhancement of upper alpha band. A user-specific training was used (upper alpha was determined for each user using the individual alpha frequency) to reduce the unspecific factors of training the entire classical alpha band as traditional NF usually does. EEG assessments in active and passive open-eyes state were conducted pre/post the NF training. The EEG analyses reveal the UA enhancement during the active tasks which is independent of other frequency bands. UA was also enhanced in the passive state but independence could not be obtained in lower alpha band. Finally, significant improvement in working memory was obtained with regard to a control group.