The advent of artificial intelligence (AI) and robotics platforms requiring human behaviors has expanded the development of neuromorphic devices. However, despite many industrial applications based on artificial intelligence have emerged in the last few years, they are mainly based on well-established technologies and classical computational paradigms. The main challenge for the next expansion of AI models is to draw inspiration from the way human brain works to develop both hardware and software platforms to emulate computation performed by neurons and synapses.
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 high-level of interdisciplinarity of this Research Topic allows to explore different areas of research which are apparently distant form each other but maintaining a common thread given by the performances shown by the nervous system, 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 AI applications will be taken into account.
The advent of artificial intelligence (AI) and robotics platforms requiring human behaviors has expanded the development of neuromorphic devices. However, despite many industrial applications based on artificial intelligence have emerged in the last few years, they are mainly based on well-established technologies and classical computational paradigms. The main challenge for the next expansion of AI models is to draw inspiration from the way human brain works to develop both hardware and software platforms to emulate computation performed by neurons and synapses.
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 high-level of interdisciplinarity of this Research Topic allows to explore different areas of research which are apparently distant form each other but maintaining a common thread given by the performances shown by the nervous system, 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 AI applications will be taken into account.