Consuming only about several watts energy, mammalian brains are able to carry out 10^15 operations per second. The biophysical mechanism of this extremely efficient energy expenditure has attracted great attention in the last decades, not only from neuroscience society, but also from the field of artificial intelligence. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy efficient neural code from the molecular level to the circuit level. The energy efficient mechanism studies may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligence in nature. It will open a new window to unveil the working principles of brains, and potentially facilitate the development of novel intelligent biology-based energy efficient technology.
In the recent literature, many significant contributions from ionic channel level to brain connectivity level have been achieved by several research groups. Both experimental and computational evidence suggests that neural systems may utilize these factors efficiently to maximize the efficiency of energy consumption in processing neural signals. Neurodegeneration related to age or diseases may bring disorders of the efficient metabolism and normal functions of ionic channels, glia and brain connectivity, and seriously degrade the energy efficient neural code.
This Research Topic aims to create a multidisciplinary forum of discussion on recent advances in energy efficient neural information processing from basic neurobiological experimental and computational modeling investigation to clinical human behavior study, as well as new applications to biology, artificial intelligence, genetics, bioengineering and clinical medicine. Submissions should show a diversity of new developments in these areas. We welcome high quality articles containing original research results and review articles of exceptional merit, with the goal of providing more information about this new multidisciplinary area of neuroscience.
Potential subjects include, but are not limited to:
• Energy efficient ionic channels.
• Energy efficient neural activity and mechanism.
• Neuromorphology and metabolism.
• Efficient synaptic transmission and plasticity.
• Energy efficient interaction between neurons and glia.
• Genetics evidences supporting efficient brain metabolism.
• Excitatory and inhibitory balanced neural network.
• Metabolic disorders in brain diseases.
• Experience and training effect on the brain functional and anatomical connectivity
• Age related metabolic change and brain functional connectivity changes.
• Develop new approaches that could intervene the decline of metabolic efficiency and neuroplasticity with age, such as effective cognitive training and TMS.
• Energy efficiency in artificial in artificial intelligence.
Consuming only about several watts energy, mammalian brains are able to carry out 10^15 operations per second. The biophysical mechanism of this extremely efficient energy expenditure has attracted great attention in the last decades, not only from neuroscience society, but also from the field of artificial intelligence. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy efficient neural code from the molecular level to the circuit level. The energy efficient mechanism studies may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligence in nature. It will open a new window to unveil the working principles of brains, and potentially facilitate the development of novel intelligent biology-based energy efficient technology.
In the recent literature, many significant contributions from ionic channel level to brain connectivity level have been achieved by several research groups. Both experimental and computational evidence suggests that neural systems may utilize these factors efficiently to maximize the efficiency of energy consumption in processing neural signals. Neurodegeneration related to age or diseases may bring disorders of the efficient metabolism and normal functions of ionic channels, glia and brain connectivity, and seriously degrade the energy efficient neural code.
This Research Topic aims to create a multidisciplinary forum of discussion on recent advances in energy efficient neural information processing from basic neurobiological experimental and computational modeling investigation to clinical human behavior study, as well as new applications to biology, artificial intelligence, genetics, bioengineering and clinical medicine. Submissions should show a diversity of new developments in these areas. We welcome high quality articles containing original research results and review articles of exceptional merit, with the goal of providing more information about this new multidisciplinary area of neuroscience.
Potential subjects include, but are not limited to:
• Energy efficient ionic channels.
• Energy efficient neural activity and mechanism.
• Neuromorphology and metabolism.
• Efficient synaptic transmission and plasticity.
• Energy efficient interaction between neurons and glia.
• Genetics evidences supporting efficient brain metabolism.
• Excitatory and inhibitory balanced neural network.
• Metabolic disorders in brain diseases.
• Experience and training effect on the brain functional and anatomical connectivity
• Age related metabolic change and brain functional connectivity changes.
• Develop new approaches that could intervene the decline of metabolic efficiency and neuroplasticity with age, such as effective cognitive training and TMS.
• Energy efficiency in artificial in artificial intelligence.
