Brain-Computer Interfaces

The brain is considered the master organ of our body and is exceptional in its capacity to perceive the information to make intelligent decisions. Mental and neural disorders represent approximately two percent of the chronically ill population and this rate is alarmingly rising. Additionally, a significant population with brain-associated problems faces disabilities associated with brain damage in their latter part of life. Identification of this information processing, (otherwise called brain informatics) is crucial for the assessment of mental health which in other ways helps in early prognosis and effective diagnosis of neural disorders. However, the greater drawback is the knowledge gap. Deciphering the function of the brain and detecting signature patterns of diseases are more complex which is proven to be inefficient through current methodologies. However, the accumulation of brain-related medical big data would revolutionize the prognosis and treatment of mental and neural disorders. This would certainly help in the development of wearable brain sensors (like wearable EEG) that facilitate remote monitoring of brain activity and greatly help in studying the signature brain activities associated with diseases which greatly increase the sophistication of prognosis. Moreover, fitness bands can be improvised with the ability to track physical activities and this would greatly help in real-time monitoring of changes in physical activities associated with diseases.  A smart amalgamation of the medical internet of things (IMoT) connected with an android app, facilitates self-assessment of conducting the regular test in neurological patients related to motor, and cognitive functions and assess their condition. They can even schedule a meeting with a doctor when the patient is in need. Furthermore, the accumulation of disease-related information would open the applicability of brain stimulators for the treatment of a myriad of previously untreatable diseases.

The detection and classification of brain-related activities rely primarily on the various medical imaging processes. However, they are inadequate to completely map the brain interaction due to potential drawbacks. Understanding the neural communication circuit for many disease conditions is not established. Moreover, changes in neural circuits for the detection of emotions (which are symptoms for the occurrence of disease) are less understood for the early prognosis of diseases. In addition, the information processing systems and neural circuits at an unconscious level, which play a vital role in human cognition are little explored. Therefore, it is mandatory to study and analyze brain informatics for early detection and treatment of many psychological disorders. Thus, the adoption of enhanced approaches in studying brain signaling and neural circuits would transform the diagnosis and treatment of many incurable diseases (like Alzheimer’s and Parkinson’s diseases). Moreover, since human cognition is set as a reference for computation abilities, brain informatics would lead to the development of novel bio-inspired algorithms that would revolutionize the analysis and interpretation of large datasets.

Therefore, this blog forms an ideal platform for researchers, medical professionals, and programmers to present their unpublished works, reviews, and perspectives on recent innovations identification and detection of brain big data for mental and neural wellbeing.  

Topics of interest include, but are not limited to, the following:

• Development of novel non-invasive sensors for mapping neural circuits
• Trends in imagery-based analysis and mapping of human emotions
• Research in structural and functional analysis of brain dynamics
• Trends in adaptation and self-organization of brain during decision making
• Innovations in novel methodologies for studying intelligent behavior
• Emerging advances in learning behavior using visual and auditory perception
• Development of advanced brain sensors for implanting signals for modulating emotions and feelings
• Emerging trends in methodologies for studying higher order cognitive functions and relationships
• Trends in mapping of neural circuits related to conscious and subconscious mental functions
• Development of innovative brain inspired deep learning methodologies for large data analysis
• Detection and analysis of potential signatures for disease detection and treatment
• Impact of brain informatics in mitigating mental breakdowns
• Trends in remote neurological assessment for monitoring disease progression

Submission Deadline of Papers - 20.02.2023

Authors Notification Date - 25.03.2024

Revised Papers Due Date - 10.05.2024

Final notification Date - 05.08.2024

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