Understanding how neural information is processed and represented by the nervous systems is key for the development of novel brain-machine interfaces and therapeutic approaches. Benefiting from high-res brain imaging, such as fMRI, single-unit recordings, invasive and non-invasive EEG, etc., more and more evidence has been obtained about neural activity patterns in various brain areas or neural tissues. However, real-time decoding of the information, which is assumed to reflect neural dynamics and plays key roles in recent brain-machine interface research, is still a challenge. Part of the reason arises from the fact that predictions are now made based on only a small amount of instantaneous data, whose information is usually not as obvious and stable as long-term statistical measures. With the arrival of large datasets and multidimensional measurements, novel processing algorithms and data-driven deep learning methods are beginning to bring new insights into neural processing patterns. On the other hand, devices based on flexible materials and novel physical mechanisms are being introduced to facilitate information exchange via the interface between the external machines and the neural tissues. These include electrode technology based on flexible and nanostructured substrate, small-sized miniature integrated neural stimulator, novel energy-efficient technology to power the neural device, wireless neural stimulation, and recording device, and wearable dry/hybrid electrodes with good skin contact. These emerging technologies are jointly and profoundly influencing the progress of brain-machine interaction research.
This research topic focuses on neural information processing advances and novel hardware technologies that potentially lead to high-efficiency interactions between the nervous systems and external devices, such as novel developments for neuromodulation technology, neuroprosthetics, and brain-machine interaction. The topic will mainly focus on how the sensory perception information and intention are represented in neural signals by novel signal processing technology, data-driven methods and how the development of novel hardware or device can enable the efficient information exchange between the external devices and the neural tissues such as flexible electrodes, novel neural stimulation technology, feedback or closed-loop system.
The scope of the topic includes:
- Neural decoding for invasive and non-invasive neural signals
- Sensory and motor information processing
- Novel electrode technology
- Miniature Integrated neural stimulator
- Wireless neural stimulation and recording device
- Novel neural signal modeling, processing and estimation
Understanding how neural information is processed and represented by the nervous systems is key for the development of novel brain-machine interfaces and therapeutic approaches. Benefiting from high-res brain imaging, such as fMRI, single-unit recordings, invasive and non-invasive EEG, etc., more and more evidence has been obtained about neural activity patterns in various brain areas or neural tissues. However, real-time decoding of the information, which is assumed to reflect neural dynamics and plays key roles in recent brain-machine interface research, is still a challenge. Part of the reason arises from the fact that predictions are now made based on only a small amount of instantaneous data, whose information is usually not as obvious and stable as long-term statistical measures. With the arrival of large datasets and multidimensional measurements, novel processing algorithms and data-driven deep learning methods are beginning to bring new insights into neural processing patterns. On the other hand, devices based on flexible materials and novel physical mechanisms are being introduced to facilitate information exchange via the interface between the external machines and the neural tissues. These include electrode technology based on flexible and nanostructured substrate, small-sized miniature integrated neural stimulator, novel energy-efficient technology to power the neural device, wireless neural stimulation, and recording device, and wearable dry/hybrid electrodes with good skin contact. These emerging technologies are jointly and profoundly influencing the progress of brain-machine interaction research.
This research topic focuses on neural information processing advances and novel hardware technologies that potentially lead to high-efficiency interactions between the nervous systems and external devices, such as novel developments for neuromodulation technology, neuroprosthetics, and brain-machine interaction. The topic will mainly focus on how the sensory perception information and intention are represented in neural signals by novel signal processing technology, data-driven methods and how the development of novel hardware or device can enable the efficient information exchange between the external devices and the neural tissues such as flexible electrodes, novel neural stimulation technology, feedback or closed-loop system.
The scope of the topic includes:
- Neural decoding for invasive and non-invasive neural signals
- Sensory and motor information processing
- Novel electrode technology
- Miniature Integrated neural stimulator
- Wireless neural stimulation and recording device
- Novel neural signal modeling, processing and estimation