Top Tweets for #Bioelectric_patterns

4 months ago

Online supervised learning of temporal patterns in biological neural networks under feedback control https://t.co/Io3WVisZFa @PNASNews #NeuroAI #BioAI #Neural_activity #Bioelectric_patterns #Lorenz_attractor Here is the summary: For decades, Neurophysiologists studied the brain to understand intelligence. Now, they are beginning to use the brain itself as a computer. In a striking set of experiments, researchers grew living rat neurons in the lab, allowing them to self-organize into a functioning biological network. These brain cells were connected to microelectrode arrays that could both read and stimulate activity, while microfluidic systems carefully controlled their environment. Using a machine learning approach known as reservoir computing, combined with a real-time training method called FORCE learning, the scientists began feeding signals into this living network—and continuously adjusting feedback based on its output. At first, the neurons fired randomly, as expected. But over time, something remarkable happened. The network started producing structured patterns: smooth sine waves, sharp square waves, even complex chaotic dynamics like the Lorenz attractor. Across timescales of seconds, the system transformed noisy biological activity into stable, predictable outputs—effectively “learning” in real time. It was living tissue behaving like a computational system. The implication is profound: neurons are not just objects of study and opening the door to hybrid systems that learn, adapt, and compute in ways we are only beginning to imagine.

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