Lecture

Neural Interfaces: Fundamentals of Neuroengineering

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In course

BIOENG-448: Fundamentals of neuroengineering

Neuroengineering is at the frontier between neuroscience and engineering: understanding how the brain works allows developing engineering applications and therapies of high impact, while the design of new measurement and data analysis techniques contribute ...

Description

This lecture covers the definition and motivations for developing neural interfaces, including those with the central and peripheral nervous systems. It discusses the design principles of invasive bidirectional neural interfaces, emphasizing the importance of safety, efficacy, and integration with neuroprostheses. The evolution of cortical interfaces from first to third generation is explored, highlighting advancements in electrode technology and materials. The lecture also delves into the challenges and innovations in regenerative and intraneural electrodes, as well as the potential of nanotechnology in creating interfaces at the subcellular level.

Instructors (2)

Solaiman Shokur

2019 - now : Senior Scientist, Translational neuroengineering Laboratory, EPFL(Geneva) Team leader: CHRONOS project, a multi-center European project that aims at developing the first chronically implanted prosthetic hand for transradial amputee patients with bidirectional communication capabilities. NCCR Robotics: Bi-directional control of supernumerary limbs.2014-2019: Research Coordinator, AASDAP (São Paulo, Brazil) Responsible for both the scientific production and the clinical protocol at the AASDAP neurorehabilitation laboratory. 2013-2014: Postdoctoral associate, Walk again project, Insituto Santos Dumond. (Natal, RN, Brazil)Head of the engineering team in charge of the system integration. 2010-2012: Visiting scientist, Nicolelis Lab (Duke University). Development and validation of a virtual-reality based brain-machine interface for rhesus monkeys. 2007 – 2010: Teaching assistant, Laboratory of Robotics Systems (EPFL)

Silvestro Micera

Short biographical sketch Silvestro Micera received the University degree (Laurea) in Electrical Engineering from the University of Pisa, in 1996, and the Ph.D. degree in Biomedical Engineering from the Scuola Superiore Sant'Anna, in 2000. From 2000 to 2009, he has been an Assistant Professor of BioRobotics at the Scuola Superiore Sant'Anna where he is now the Head of the Neural Engineering group. In 2007 he was a Visiting Scientist at the Massachusetts Institute of Technology, Cambridge, USA with a Fulbri

Official source

Ontological neighbourhood

Biology

Anatomy: Neuroanatomy

Related concepts (32)

Brain–computer interface

A brain–computer interface (BCI), sometimes called a brain–machine interface (BMI) or smartbrain, is a direct communication pathway between the brain's electrical activity and an external device, most commonly a computer or robotic limb. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions. They are often conceptualized as a human–machine interface that skips the intermediary component of the physical movement of body parts, although they also raise the possibility of the erasure of the discreteness of brain and machine.

Neural engineering

Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, or enhance neural systems. Neural engineers are uniquely qualified to solve design problems at the interface of living neural tissue and non-living constructs (Hetling, 2008). The field of neural engineering draws on the fields of computational neuroscience, experimental neuroscience, neurology, electrical engineering and signal processing of living neural tissue, and encompasses elements from robotics, cybernetics, computer engineering, neural tissue engineering, materials science, and nanotechnology.

Somatic nervous system

The somatic nervous system (SNS), or voluntary nervous system is the part of the peripheral nervous system associated with the voluntary control of body movements via skeletal muscles. The somatic nervous system consists of nerves carrying afferent nerve fibers, which relay sensation from the body to the central nervous system (CNS), and nerves carrying efferent nerve fibers, which relay motor commands from the CNS to stimulate muscle contraction. The a- of afferent and the e- of efferent correspond to the prefixes ad- (to, toward) and ex- (out of).

Autonomic nervous system

The autonomic nervous system (ANS), formerly referred to as the vegetative nervous system, is a division of the nervous system that supplies internal organs, smooth muscle and glands. The autonomic nervous system is a control system that acts largely unconsciously and regulates bodily functions, such as the heart rate, its force of contraction, digestion, respiratory rate, pupillary response, urination, and sexual arousal. This system is the primary mechanism in control of the fight-or-flight response.

Nanotechnology

Nanotechnology, often shortened to nanotech, is the use of matter on atomic, molecular, and supramolecular scales for industrial purposes. The earliest, widespread description of nanotechnology referred to the particular technological goal of precisely manipulating atoms and molecules for fabrication of macroscale products, also now referred to as molecular nanotechnology. A more generalized description of nanotechnology was subsequently established by the National Nanotechnology Initiative, which defined nanotechnology as the manipulation of matter with at least one dimension sized from 1 to 100 nanometers (nm).

Related lectures (64)

Neural Interfaces: Electrodes

Delves into the world of neural interfaces, focusing on the implementation of invasive and non-invasive electrodes and the evolution of electrode technologies.

Peripheral sensory feedback

Explores the importance and organization of sensory feedback in the peripheral nervous system, including artificial implementations.

Optimization of Neuroprosthetic Systems

Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.

Neural Signals and Signal Processing

Explores neural signal processing for brain-computer interfaces, including decoding techniques like Kalman filters and spike sorting.