Combining AI and neuroscience to detect and predict neurological disorders ArtificialIntelligence AI Neurology Neuroscience Brain Meningitis Neurons Speech Technology Sensors_MDPI ficialbdu UniCreativeArts cardiffmet
By Neha MathurMar 15 2023Reviewed by Benedette Cuffari, M.Sc. In a recent article published in the journal Sensors, researchers perform a scoping review on the shared relationship between artificial intelligence and neuroscience, emphasizing their convergence and possible applications.
Background Neuroscience principles have uplifted the AI field and vice versa. For example, neuroscience has helped researchers validate existing AI-based models. Likewise, biological neural networks have helped develop deep neural network architectures with several applications, such as text processing and speech recognition.
Overall, owing to the ability of AI to analyze complex data and extract hidden patterns, this technology appears to be the ideal choice for neuroscience data analysis. Neuroscience eBook Compilation of the top interviews, articles, and news in the last year. Download a free copy The human brain's working memory feature inspired scientists to design a recurrent neural network . The RNN architecture allowed the use of the past output as input to predict the subsequent output. Notably, one type of RNN known as the long short-term memory network can handle long-term dependencies, such as those that exist in text summarization.
As an alternative, spiking neural networks are being developed, as they work like biological neurons and are more energy efficient. SNNs transmit information in the form of an electric signal to another artificial neuron when its membrane potential hits a particular threshold.
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