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Generative AI can decode human memories and imagination.

    Generative AI can decode human memories and imagination. 

The breakthrough in generative AI use in mind-reading is now at least at the door. The generative AI can read memories and imagination. And that thing brings new research opportunities. Maybe quite soon. Researchers can see other people's memories and dreams from their screens. Complete knowledge of the systems is a requirement for control and benefit, and BCI (Brain-Computer Interface) is no exception. 

The ability to see what people dream gives new types of opportunities for the R&D process. The idea is that the BCI injects some model into the brain, and then the person will handle it while sleeping. This kind of new ability to decode human memories and imagination can make it possible to solve why we see dreams. And it can also open new lines for criminal investigation. 

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"UCL researchers used generative AI to model brain functions, uncovering how memories are formed, replayed, and used for imagination. The study emphasizes the reconstructive and predictive nature of memory, offering new perspectives on human cognition. Credit: SciTechDaily.com" (ScitechDaily,Decoding Human Memory and Imagination With Generative AI)

"Recent research discovers that our ability to distinguish similar memories improves over time due to the dynamic nature of engrams, brain cells involved in memory storage. This finding provides key insights into the treatment of memory disorders. Credit: SciTechDaily.com" (ScitechDaily, Unraveling Memory’s Molecular Mystery: How Brain Cells Stabilize Information Over Time)


"MIT researchers have identified unique electrical activity patterns in the brain’s cortical layers, consistent across different species. This discovery, showing faster oscillations in superficial layers and slower ones in deeper layers, provides insights into brain functioning and disorders. Credit: SciTechDaily.com" (ScitechDaily, Rhythms of the Mind: MIT Neuroscientists Reveal Universal Brain Wave Patterns)


"A recent study reveals that strong neural connections in the brain, crucial to its functionality, are likely formed by universal self-organizing principles, not species-specific mechanisms. This finding, based on advanced imaging and a Hebbian plasticity model, could reshape our understanding of brain structure in various species. Credit: SciTechDaily.com" (ScitechDaily.com, Brain Connectivity Breakthrough: Similar Neural Network Patterns Discovered Across Diverse Species)

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The process that brought this ability to read people's minds consists of AI solving the memory's molecular vortex. And that thing opened the road for the generative AI to decode the brain's imagination and memories. And that ability brings new types of things, that people can use in many operations. Solving the molecular mystery of how memory stores and selects information that brains store brings new abilities for researchers. 

If we think, that the brain's internal language is universal. That means we can read the minds of other species. In that model, we could decode the brain signals of another species by using the same methods as human mind-reading. The universal brainwave patterns tell that all people have a brain, that speaks the same language. But is it possible that also other species have the same kind of universal language, and could that universal language be the same with humans and other species? 

There is the possibility that all species have the same brain internal language. In all species, the brain has similar neural patterns. And if that thing means that the brain's internal language is always the same. That thing brings awesome possibilities for researchers. The BCI systems can help people communicate with each other silently using brain waves. 

Or at least people can simply move their lips and speak whisperly. Then the brainwave reader reads the EEG from the Wernicke-lobe. Then the receiver can transfer that data to the receiver's Broca lobe. The same system can used to control the BCI systems. The system decodes that EEG for a modified "speech to text" application. And then that application sends those texts for generative AI. Similar systems can also used to give orders for animals. 



https://scitechdaily.com/decoding-human-memory-and-imagination-with-generative-ai/ 


https://scitechdaily.com/unraveling-memorys-molecular-mystery-how-brain-cells-stabilize-information-over-time/


https://scitechdaily.com/brain-connectivity-breakthrough-similar-neural-network-patterns-discovered-across-diverse-species/

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