{"id":246718,"date":"2026-10-14T13:31:34","date_gmt":"2026-10-14T13:31:34","guid":{"rendered":"https:\/\/yogaesoteric.net\/?p=246718"},"modified":"2026-10-14T13:31:34","modified_gmt":"2026-10-14T13:31:34","slug":"the-end-of-the-last-private-hurdle-ai-can-now-read-consciousness-israeli-researchers-translate-brain-activity-into-images","status":"publish","type":"post","link":"https:\/\/yogaesoteric.net\/en\/the-end-of-the-last-private-hurdle-ai-can-now-read-consciousness-israeli-researchers-translate-brain-activity-into-images\/","title":{"rendered":"The end of the last private hurdle: AI can now \u201cread consciousness\u201d \u2013 Israeli researchers translate brain activity into images"},"content":{"rendered":"

What a person sees can increasingly be reconstructed from their brain activity. Researchers at the Weizmann Institute<\/a> for Science in Israel have developed Brain-IT, an AI model that can generate images from fMRI scans of the brain that are astonishingly close to the actual subject being viewed. The institute itself refers to this as a new science of \u201cconsciousness reading<\/em>.\u201d<\/p>\n

\"\"<\/p>\n

However, the technology doesn’t read thoughts in the traditional sense. Brain-IT analyses the brain activity of people while they view images. Functional magnetic resonance imaging (fMRI) records modifications in blood flow and oxygen supply to different brain regions, from which activity patterns can be derived.<\/p>\n

Professor Michal Irani’s team developed a method that identifies functionally similar areas in different brains. Brain-IT assigns the measured brain signals to common functional clusters and then links this information to features of the perceived image. A diffusion model then generates a visual reconstruction from this data.<\/p>\n

Only one more hour of brain data<\/strong><\/p>\n

A crucial advancement lies in the speed with which Brain-IT can be adapted to a new person.<\/p>\n

Previous methods sometimes require dozens of hours of brain scans. According to the researchers, Brain-IT achieves results comparable to previous models trained with around 40 hours of data, using only one hour of fMRI data from a new test subject. In trials, recognizable reconstructions were even produced with just 15 minutes of data.<\/p>\n

The model doesn’t simply try to guess whether someone is looking at, for example, a person, an animal, or a building. It combines semantic information about the image content with structural features such as spatial arrangement. Brain-IT is said to be superior to previous methods, especially when it comes to colour, composition, and details.<\/p>\n

The process also works in the other direction.<\/p>\n

What is particularly interesting is that the researchers are not only translating brain activity into images.<\/p>\n

The team also works with a so-called brain encoder, which takes the opposite approach: An image is presented and the model attempts to predict which activity patterns this image would trigger in the human brain.<\/p>\n

According to Irani, during its development the system identified 128 functional regions or clusters that perform comparable tasks in the processing of visual information in different people \u2013 even if their exact anatomical position differs from person to person.<\/p>\n

This research goes beyond a spectacular image reconstruction. It could provide new insights into how different human brains process visual information.<\/p>\n

From seeing to actually \u201cconsciousness reading\u201d?<\/strong><\/p>\n

Brain-IT currently primarily reconstructs images that a person actually sees. Therefore, the term \u201cconsciousness reading<\/em>\u201d should not be confused with the free reading of arbitrary thoughts.<\/p>\n

But the direction of development is remarkable.<\/p>\n

The researchers want to go beyond static images. In the future, methods for more complex visual and other sensory information are conceivable. This brings us closer to the question of whether similar systems could one day reconstruct inner thoughts or other psychic content.<\/p>\n

The Weizmann Institute itself explicitly places Brain-IT under the heading \u201cThe New Science of Mind-Reading<\/em>\u201d and describes the model as an AI that can \u201cread<\/em>\u201d brain activity and reconstruct what a person sees.<\/p>\n

Medical opportunities \u2013 but also a new boundary of privacy<\/strong><\/p>\n

The medical benefits of such technologies could be enormous. Brain-computer interfaces, for example, could help people who can no longer speak or communicate due to severe paralysis. Systems that translate brain activity into speech or other signals already exist.<\/p>\n

Brain-IT now shows how quickly this development is progressing: Instead of building a new system for each person with enormous amounts of personal brain data, the AI tries to recognize common patterns between different human brains and transfer this knowledge to new people.<\/p>\n

But this also raises a sensitive long-term question: How private will our brain data remain if AI becomes increasingly adept at deriving perceptions and potentially more complex mental content from it?<\/p>\n

Brain-IT is still a long way from being able to secretly read a person’s thoughts. Current experiments require high-quality fMRI scans, which are produced in a large magnetic resonance imaging scanner. Therefore, it’s impossible to speak of an unnoticed \u201cthought scanner<\/em>.\u201d<\/p>\n

But the direction of research is clear: AI is beginning to translate measurable brain activity back into information understandable to other people with increasing precision.<\/p>\n

What is today still the reconstruction of an actually viewed image could thus be only the beginning of a development that, in the long term, will touch upon one of the most private boundaries of mankind: the processes in one\u2019s own brain.<\/p>\n

 <\/p>\n

yogaesoteric
\nOctober 14, 2026<\/strong><\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

What a person sees can increasingly be reconstructed from their brain activity. Researchers at the Weizmann Institute for Science in Israel have developed Brain-IT, an AI model that can generate images from fMRI scans of the brain that are astonishingly close to the actual subject being viewed. The institute itself refers to this as a […]<\/p>\n","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[1369],"tags":[],"class_list":["post-246718","post","type-post","status-publish","format-standard","hentry","category-science-technology-1602-en"],"_links":{"self":[{"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/posts\/246718","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/comments?post=246718"}],"version-history":[{"count":1,"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/posts\/246718\/revisions"}],"predecessor-version":[{"id":246722,"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/posts\/246718\/revisions\/246722"}],"wp:attachment":[{"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/media?parent=246718"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/categories?post=246718"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/yogaesoteric.net\/en\/wp-json\/wp\/v2\/tags?post=246718"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}