A groundbreaking study from researchers at the Massachusetts Institute of Technology (MIT) suggests that astrocytes\u2014star-shaped brain cells long considered to be little more than passive support tissue\u2014may play a direct role in memory storage and computation. Published in the Proceedings of the National Academy of Sciences, the research challenges traditional neuron-only models of the brain. For decades, conventional theories of memory have relied on Hopfield networks, which distribute memories across connections between neurons. However, these systems face a distinct architectural ceiling, resulting in memory interference once a finite capacity is reached. While advanced mathematical models known as “dense associative memories” can bypass these limits, they require complex, higher-order interactions among multiple neurons simultaneously\u2014a feat standard biological synapses cannot achieve on their own.\u00a0\u00a0<\/p>\n\n\n\n
Led by author Leo Kozachkov alongside Jean-Jacques Slotine (MIT professor of mechanical engineering and brain and cognitive sciences) and Dmitry Krotov (MIT-IBM Watson AI Lab), the team proposed a new model where astrocytes fill this computational gap. Unlike neurons, astrocytes do not rely on electrical impulses, communicating instead through calcium-based signaling and the release of chemical messengers called gliotransmitters. Because a single astrocyte extends thousands of fine processes that wrap around individual synapses\u2014forming what scientists call “tripartite synapses”\u2014they are perfectly positioned to act as integrated processing units. By actively participating in the dialogue between multiple neurons, these cell networks can facilitate the higher-order interactions required for dense associative memory. Intriguingly, the MIT model suggests that this combined network allows storage capacity to scale proportionally with the overall size of the network, indicating that human memory may possess a architecture capable of supporting vastly more information than previously thought possible.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"
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