Neural engineering integrates concepts from neuroscience, engineering, physics, computer science, and mathematics to comprehend and influence the functions of the nervous system. It encompasses various aspects, including neural prosthetics, neural imaging, neural computation, and neural interface technologies. Neural prosthetics involve the development of devices or systems that can replace or enhance the functions of the nervous system. This includes brain-computer interfaces (BCIs), which enable direct communication between the brain and external devices, allowing individuals to control computers, prosthetic limbs, or other devices using their thoughts. Neural prosthetics hold promise for restoring lost sensory or motor functions in individuals with disabilities. Neural imaging techniques enable scientists to visualize and understand the structure and function of the nervous system. Methods such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) provide insights into brain activity and connectivity, aiding in the diagnosis and treatment of neurological disorders. Neural computation involves the development of algorithms and computational models inspired by the structure and function of the brain. These models are used to simulate neural processes, understand neural dynamics, and develop artificial intelligence systems capable of learning and adapting. Neural interface technologies focus on creating bi-directional communication pathways between the nervous system and external devices. This includes implantable devices, such as deep brain stimulators used to treat Parkinson's disease, as well as non-invasive techniques like transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) for modulating brain activity. Overall, neural engineering plays a crucial role in advancing our understanding of the brain and developing innovative solutions for neurological disorders, brain-computer communication, and enhancing human capabilities. Its interdisciplinary nature fosters collaboration across diverse fields to tackle complex challenges at the intersection of biology and technology.
Title : Scalp acupuncture with functional electrical stimulation for the treatment children with autism spectrum disorder
Zhenhuan Liu, Guangzhou University of Chinese Medicine, China
Title : Perception and individuality in patient cases identifying the ongoing evolution of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)
Ken Ware, NeuroPhysics Therapy, Australia
Title : A structure-based strategy to target pathogenic α-synuclein in Parkinson’s disease
Salvador Ventura, Autonomous University of Barcelona, Spain
Title : Rabies: Challenges in taming the beast
Alan C Jackson, University of Calgary, Canada
Title : Designing and managing intelligent and ethical transformed health and social care ecosystems
Bernd Blobel, University of Regensburg, Germany
Title : Understanding Alzheimer's disease biomarkers across diverse populations - Opportunities and Insights for novel prevision medicine approaches
Sid O Bryant, Texas College of Osteopathic Medicine and University of North Texas Health Science Center Fort Worth, United States