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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.
January 11, 2021
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EEG systems capture information about many different aspects of our cognition, behavior, and emotions. The technology not only helps to study the brain, but also has applications in health, in affective and emotional monitoring, and in human improvement. However, EEG data is not easy to interpret: it has a lot of noise, varies significantly between individuals and, even for the same person, changes substantially over time.
One of the main concerns when dealing with electroencephalographic signals (EEG) is assuring that we record clean data with a high signal to noise ratio. The EEG signal amplitude is in the microvolts range and it is easily contaminated with noise, known as “artifacts”, which need to be filtered from the neural processes to keep the valuable information we need for our applications. We review in this post different EEG artifacts and the main tools and techniques to remove them.
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.
When choosing an electroencephalogram (EEG) device within the constraints of a project requirements, it is important to find the maximum performance possible by balancing features and value. This article will build on top of the previous one (EEG sensor layer) by addressing important EEG amplifier features like sampling rate, bandwidth, noise level, CMRR, etc.
Quantitative electroencephalogram (QEEG) is the mathematical analysis of the brain’s electrical activity, mainly power spectral analyses, to obtain metrics that may be associated with behavioral-cognitive function.
When choosing an electroencephalogram (EEG) device within the constraints of a project requirements, it is important to find the maximum performance possible by balancing features and value. This article focuses on the EEG sensor layer features, including the type of sensor (dry/wet), shielding, and electrode placement, in order to give guidelines to help in the selection process.
Dry-EEG systems can open the door for the application of neuroscience in real-world settings, and the market to a new generation of products and services based on neurotechnology. However, there are many open questions related to their reliability, accuracy and signal quality. This post will give the reader solid arguments for selecting a technology that fits the application requirements.
Brain-computer interfaces (BCI) occupy an emerging field with the potential of changing the world, with diverse applications from rehabilitation to human augmentation. In this post, we will provide some insights into what BCIs are, how they are built, and what are the most promising applications that may be available in the near future.
More and more people wish to improve their academic or professional performance by training their cognitive capabilities. This means improving cognitive functioning until each person’s optimal. Do you know what cognitive performance is and how it can be trained? This post will provide more information on high cognitive performance and the most frequent techniques employed to achieve it.
Usually, cognitive deterioration is one of the most common subjects discussed in primary care. This condition progressively evolves with age, and requires specific interventions to be reverted, improving cognitive performance. Cognitive rehabilitation has the objective of improving cognitive functions such as memory, attention and language, which have a great impact on the life of patients. We summarize within this post the most common cognitive rehabilitation strategies and application areas.
Cognitive stimulation starts to open its way as a tool to care for the mental health of people. For such, professionals should receive adequate training and have the necessary knowledge to employ it and obtain positive results but… what should I keep in mind at the time of choosing a cognitive stimulation workshop? We’ll cover that.
According to the World Health Organization (WHO), depression affects more than 300 million people in the world, being considered a frequent mental disorder. The emotional symptoms are usually the first to be treated with current existing treatments, but how can we intervene on the cognitive impairment that often affects the people that suffer from depression?
Cars connected to the mind, implants in the brain to cure Alzheimer's or letters that are written just by thinking about it are some of the advances on which neurotechnology is working. Brain-machine interfaces (BCI systems) will completely change the way we live, but are we aware of the ethical issues and implications that these developments will involve?
We believe that reality is exactly what we perceive but really, this is just an illusion of our own brain. This happens because our brain takes shortcuts to interpret information and adapt to our surroundings: heuristics on which the brain relies to understand the reality perceived, but… can we always trust our brain when it utilizes these resources?
Neuromarketing is a new discipline that complements marketing research and makes use of scientific laboratories and techniques such as brain imaging (with EEG), implicit response tests, eye-tracking and facial coding, to name a few. Do you know all the existing techniques, their advantages, and limitations?
