نوار مغزی سیار و پتانسیل آن برای ترویج تئوری و کاربرد توانبخشی موتور مبتنی بر تصویرسازی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|29667||2014||6 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Psychophysiology, Volume 91, Issue 1, January 2014, Pages 10–15
Studying the brain in its natural state remains a major challenge for neuroscience. Solving this challenge would not only enable the refinement of cognitive theory, but also provide a better understanding of cognitive function in the type of complex and unpredictable situations that constitute daily life, and which are often disturbed in clinical populations. With mobile EEG, researchers now have access to a tool that can help address these issues. In this paper we present an overview of technical advancements in mobile EEG systems and associated analysis tools, and explore the benefits of this new technology. Using the example of motor imagery (MI) we will examine the translational potential of MI-based neurofeedback training for neurological rehabilitation and applied research.
Understanding human behavior is one of the big challenges for humankind. In the last 20 years neuroscience has emerged as a key area of research and there is a recognition that understanding brain function in general, and brain–behavior relationships in particular, is vital to advance solutions for major public health issues such as mental health, dementia, obesity, or impairments remaining after suffering from stroke or traumatic brain injury. Immense improvements in the availability of neuroimaging methodologies together with high-profile initiatives, such as the decade of the brain, have brought a wealth of new insights into brain function and are already leading to new forms of treatment. However, a major challenge still is to understand the brain in its natural state. This would not only enable the refinement of cognitive theory but also to get a true understanding of cognitive function in the type of complex and unpredictable situations that constitute daily life. For example, how does our brain enable us to function in a highly complex situation such as navigating through a grocery shop while selecting products from a vast range of goods? How are these processes influenced by internal physiological states such as hunger or low mood? How does our brain help us to prioritize some actions and inhibit others? What are the brain correlates of impaired, challenging or maladaptive behavior expressed in typical life situations? These are of course hugely demanding questions, which cannot be easily answered. Yet with the mobile electroencephalogram (EEG), researchers now have a tool to explore these questions. In contrast to all other techniques presently available, mobile EEG truly allows us to take neuroscience into the field and study everyday brain function. In this paper we will examine the benefits of mobile EEG and the challenges it has to meet to provide a fully fledged research tool in cognitive and clinical neuroscience, as well as a tool for clinical interventions and BCIs. We will exemplarily show how the technical challenges involved in mobile EEG have been addressed by recent advancements in the field. The focus will then be shifted to yet another opportunity associated with mobile EEG, which is the support of brain computer interface (BCI) based treatment delivery in the home environment. This will be done through the example of motor imagery (MI).
نتیجه گیری انگلیسی
Mobile EEG is an exciting new technology with excellent potential for translational and applied research. However, to fulfill this potential EEG systems must not only be small and suitable for everyday settings, but also need to produce the data quality required for single trial analysis. One particularly exciting application of mobile EEG is neurofeedback training for MI and/or motor-imagery based BCIs. Initial evidence suggests that neurofeedback can increase MI effectiveness and helps patients to learn effective MI strategies. At the same time such knowledge will help to better characterize motor control and action representation and as such aids to refine theoretical approaches as well as clinical applications.