Science & Research

Sleep is a natural behavior that forms part of our daily routine. It can be found in virtually the entire animal kingdom and plays a fundamental role in people's well-being. During sleep, a significant number of brain and body functions remain active for restorative purposes. Without enough sleep, the homeostasis of the sleep-wake cycle is seriously compromised, which can result in a number of disorders directly affecting cognitive performance and physical health.

Bitbrain's mission is to boost real-world neurotechnology research and applications that enhance people's lives. For this reason, we opened a Call for Research Projects to support research teams that are exploring neuroscience in real-world settings.

Neurorehabilitation and assistive technologies use brain-computer interfaces (BCIs) to involve the central nervous system in the rehabilitation process or to allow control of technology. Moving BCI-based neurorehabilitation or motor restoration applications from the laboratory to home settings will improve accessibility to therapies and assistive applications. This will increase potential benefits and allow a more intensive data collection to foster scientific progress.

Electroencephalography (EEG)-based neurotechnology not only offers us new alternatives to interact with our environment directly via our brain, but also promises to improve our human functions. In this post, we will discuss how to exploit these technologies as a rehabilitative tool for people with nervous system damage, and how to facilitate human enhancement for the general population.

Eye tracking has become an invaluable tool for understanding attention, visual behavior and human behavior in a number of diverse fields, from psychology, neurophysiology, user experience, market research/neuromarketing, etc. The technology can also be used for medical analysis and screening, and it provides a new method of interaction. Historically, eye tracking systems were invasive and immobile, and therefore useful only in very limited experiments. While there are still some limitations

Implicit measures became very popular years ago by the academics, and many researchers employed them to analyze biases in racial groups, gender, sexuality, age, and religion, as well as to assess self-esteem in clinical psychology. Today, other applications in market research have emerged to gather information on implicit preferences of products, brands, politicians, and celebrities, and to reveal which attributes are more inherently associated with these concepts.