The development of neuromorphic devices has been boosted by the advent of artificial intelligence and robotics platforms requiring human behaviors. Nonetheless, despite several industrial applications based on AI have emerged in the last few years, they are mainly based on well-established technologies and classical computational paradigms. The next generation of AI models is demanding inspiration from the way human brain works to develop hardware and software platforms emulating neurons and synapses, both in terms of energy consumption and computational capacity.
In this research topic, we will explore different aspects of neuromorphic computing, from experimental and computational neurophysiology to synaptic and neuromorphic electronics feeding the last generation of artificial neural networks. The present research topic has a high level of interdisciplinarity requiring to explore different areas of research apparently distant from each other while maintaining a common thread given by the performances shown by the brain, from energy consumption to highly parallelized cognitive tasks.
We will host articles focused on the analysis of the computational properties of neural microcircuits and networks as well as investigating computational paradigms exploited by neural circuits. Furthermore, works presenting new neuromorphic electronic devices and architectures are more than welcome. Articles showing neuromorphic materials mimicking synaptic and neuronal behaviors will be published. In addition, theoretical studies investigating the amazing capabilities of human brain and suggesting new computational paradigms to be employed in modern artificial intelligence applications will be taken into account. Research articles are encouraged to be submitted as well as review, mini-review and perspective manuscripts.
The development of neuromorphic devices has been boosted by the advent of artificial intelligence and robotics platforms requiring human behaviors. Nonetheless, despite several industrial applications based on AI have emerged in the last few years, they are mainly based on well-established technologies and classical computational paradigms. The next generation of AI models is demanding inspiration from the way human brain works to develop hardware and software platforms emulating neurons and synapses, both in terms of energy consumption and computational capacity.
In this research topic, we will explore different aspects of neuromorphic computing, from experimental and computational neurophysiology to synaptic and neuromorphic electronics feeding the last generation of artificial neural networks. The present research topic has a high level of interdisciplinarity requiring to explore different areas of research apparently distant from each other while maintaining a common thread given by the performances shown by the brain, from energy consumption to highly parallelized cognitive tasks.
We will host articles focused on the analysis of the computational properties of neural microcircuits and networks as well as investigating computational paradigms exploited by neural circuits. Furthermore, works presenting new neuromorphic electronic devices and architectures are more than welcome. Articles showing neuromorphic materials mimicking synaptic and neuronal behaviors will be published. In addition, theoretical studies investigating the amazing capabilities of human brain and suggesting new computational paradigms to be employed in modern artificial intelligence applications will be taken into account. Research articles are encouraged to be submitted as well as review, mini-review and perspective manuscripts.
