Featured Image

Neurofeedback Difficulty and Mental Effort

In sports training, a good way to set the intensity of a training session is according to your ability. If you train too hard, go softer. If you train too soft, go harder. This approach seems intuitive. Difficulty adaptation based on actual challenge seems sensible. But how can challenge be measured objectively? When is the… Read more »

Featured Image

The first shadowrunner

As a teenager, i was hooked on cyberpunk. One of the core aspects of the cyberpunk genre is to live outside of government and corporate control as some kind of shadow-running outlaw, and using custom-made electronics and self-written software to jack into cyberspace, hack into secure systems and fight powerful AIs. Many, including me, consider… Read more »

Featured Image

On being challenged adequately by a restorative BCI

The utility of a restorative BCI depends not only on machine learning measures like classification accuracy, but also on how the subject experiences the intervention. Roughly a quarter of subjects appear to suffer from BCI-illiteracy, i.e. they have difficulty when trying to control a BCI. An interesting question is whether they differ in their experience… Read more »

Featured Image

On exploiting the cue from cue-paced, synchronous BCIs

Many BCIs are cue-paced, i.e. they signal the start and end of the control phase to the user. Because this gives the BCI a task-like structure, such a synchronous approach is not very useful for assistive applications. Yet, there are several benefits of such a task-structure, which makes this approach very applicable for restorative BCIs… Read more »

Featured Image

Bridging the gap between motor imagery and motor execution with a brain-robot interface

Motor imagery and motor execution both cause similar changes in brain oscillations over spatially almost identical cortical areas. Because of this finding, motor imagery has been suggested as a backdoor to the motor system in stroke rehabilitation.  Yet, neuroimaging and lesion studies suggest that the networks involved in motor imagery and execution are at least… Read more »

Featured Image

Reinforcement learning for adaptive threshold control of restorative brain-computer interfaces

Restorative brain-computer interfaces (BCI) provide feedback of neuronal states to normalize pathological brain activity and achieve behavioral gains. Adaptive algorithms have proven to be powerful for assistive BCIs, but their inherent class switching clashes with the operant conditioning goal of restorative BCIs. Due to the treatment rationale of restorative BCIs, the classifier should be limited… Read more »

Featured Image

Restorative or assistive BCI? The Argument for a constrained feature space

There is a major aspect which i believe is especially prevalent in the area of BCI for Stroke Rehab. It is the apparent gap between how Brain-computer-Interface (BCI) people, mostly recruited from mathematics and engineering departments and the Neurofeedback (NFB) people, mostly recruited from practitioners and psychologists understand the treatment. In my opinion this distinction… Read more »