Review of neural network applications in sleep research.
نویسندگان
چکیده
To find a better automated sleep-wake staging system for human analyses of numerous polygraphic records is an interesting challenge in sleep research. Over the last few decades, many automated systems have been developed but none are universally applicable. Improvements in computer technology coupled with artificial neural networks based systems (connectionist models) are responsible for new data processing approaches. Despite extensive use of connectionist models in biological data processing, in the past, the field of sleep research appeared to have neglected this approach. Only a few sleep-wake staging systems based on neural network technology have been developed. This paper reviews the current use of artificial neural networks in sleep research. Following a brief presentation of neural network technology, each of the existing system is described and attention drawn to the heterogeneity of the different processing approaches in sleep research. The high performances observed with systems based on neural networks highlight the need to integrate these tools into the field of sleep research.
منابع مشابه
Artificial neural networks: applications in predicting pancreatitis survival
Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...
متن کاملArtificial neural networks: applications in predicting pancreatitis survival
Artificial neural networks are intelligent systems that have successfully been used for prediction in different medical fields. In this study, the efficiency of a neural network for predicting the survival of patients with acute pancreatitis is compared with days-of-survival obtained from patients. A three- layer back-propagation neural network was developed for this purpose. Clinical data (e.g...
متن کاملReinforcement Learning in Neural Networks: A Survey
In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...
متن کاملReinforcement Learning in Neural Networks: A Survey
In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...
متن کاملA neural mass model of CA1-CA3 neural network and studying sharp wave ripples
We spend one third of our life in sleep. The interesting point about the sleep is that the neurons are not quiescent during sleeping and they show synchronous oscillations at different regions. Especially sharp wave ripples are observed in the hippocampus. Here, we propose a simple phenomenological neural mass model for the CA1-CA3 network of the hippocampus considering the spike frequency adap...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Journal of neuroscience methods
دوره 79 2 شماره
صفحات -
تاریخ انتشار 1998