Research working towards creating biocomputers made from human brain organoids could better understanding of neurological conditions.
So much here I never knew:
Dr. Axel Montagne is a chancellor’s fellow and group leader at the UK Dementia Research Institute at the University of Edinburgh Centre for Clinical Brain Sciences. His group aims to understand how, when, and where critical components of the blood-brain barrier become dysfunctional preceding dementia and in the earliest stages of age-related cognitive decline. With this knowledge, they hope to develop precise treatments targeting brain vasculature to protect brain function.
There is this picture—you may have seen it. It is black and white and has two silhouettes facing one another. Or maybe you see the black vase with a white background. But now, you likely see both.
It is an example of a visual illusion that reminds us to consider what we did not see at first glance, what we may not be able to see, or what our experience has taught us to know—there is always more to the picture or maybe even a different image to consider altogether. Researchers are finding the process in our brain that allows us to see these visual distinctions may not be happening the same way in the brains of children with autism spectrum disorder. They may be seeing these illusions differently.
“How our brain puts together pieces of an object or visual scene is important in helping us interact with our environments,” said Emily Knight, MD, Ph.D., assistant professor of Neuroscience and Pediatrics at the University of Rochester Medical Center, and first author on a study out today in the Journal of Neuroscience. “When we view an object or picture, our brains use processes that consider our experience and contextual information to help anticipate sensory inputs, address ambiguity, and fill in the missing information.”
Neuroscience research just got a little bit easier, thanks to the release of tens of thousands of images of fruit fly brain neurons generated by Janelia’s FlyLight Project Team.
Over eight years, the FlyLight Project Team and collaborators dissected, labeled, and imaged the neurons of more than 74,000 fruit fly brains, taken from more than 5,000 different genetically modified fly strains.
Now, these images are being made freely available, enabling scientists to quickly and easily find the neurons they need to test theories about how the nervous system works.
Trying to make computers more like human brains isn’t a new phenomenon. However, a team of researchers from Johns Hopkins University argues that there could be many benefits in taking this concept a bit more literally by using actual neurons, though there are some hurdles to jump first before we get there.
In a recent paper, the team laid out a roadmap of what’s needed before we can create biocomputers powered by human brain cells (not taken from human brains, though). Further, according to one of the researchers, there are some clear benefits the proposed “organoid intelligence” would have over current computers.
“We have always tried to make our computers more brain-like,” Thomas Hartung, a researcher at Johns Hopkins University’s Environmental Health and Engineering department and one of the paper’s authors, told Ars. “At least theoretically, the brain is essentially unmatched as a computer.”
You can easily picture yourself riding a bicycle across the sky even though that’s not something that can actually happen. You can envision yourself doing something you’ve never done before – like water skiing – and maybe even imagine a better way to do it than anyone else.
Imagination involves creating a mental image of something that is not present for your senses to detect, or even something that isn’t out there in reality somewhere. Imagination is one of the key abilities that make us human. But where did it come from?
I’m a neuroscientist who studies how children acquire imagination. I’m especially interested in the neurological mechanisms of imagination. Once we identify what brain structures and connections are necessary to mentally construct new objects and scenes, scientists like me can look back over the course of evolution to see when these brain areas emerged – and potentially gave birth to the first kinds of imagination.
Meta’s AR glasses could be launched in 2027.
Mark Zuckerberg’s Meta Platforms is doubling down on its virtual reality (VR) products and plans to rope in augmented reality (AR) experiences. It looks to define its position in the technology industry a few years from now. Thousands of employees of the Reality Labs Division at Meta were recently presented with a roadmap for the company’s products, which was then shared with The Verge.
VR, AR, and neural interfacesAlthough Zuckerberg has spoken mainly of the metaverse that the company would build as the future of the internet, Meta now seems to have taken its foot off the pedal to make the metaverse itself and focus on the tools instead and improving them.
Continue reading “Meta works on a flurry of AR/VR devices over the next 3 to 4 years” »
A new paper has been released that outlines a type of ‘roadmap’ for biocomputers – computers drawing memory and power from human neurons – or brain cells.
The crux of the new work is a term called ‘organoid intelligence’ – this is the idea that a small group of human neurons could begin understanding it’s environment, learn and remember.
But to understand this, we first have to look to what an organoid is and how they are made.
Bruce Willis has FTD. I always wondered if gene therapy could help. Apparently so did Passage Bio, and they are doing clinical trials.
FTD is a disorder that affects the frontal and temporal lobes of the brain, areas that control personality, executive function, and language. FTD is a form of early onset dementia and currently has no approved disease-modifying therapies. In approximately 5–10% of individuals with FTD, the disease occurs because of mutations in the GRN gene. These mutations cause a deficiency of progranulin that helps regulate cellular processes.
Continue reading “Gene Therapy Clinical Trial for Frontotemporal Dementia Has Begun” »
Is self-consciousness necessary for consciousness? The answer is yes. So there you have it—the answer is yes. This was my response to a question I was asked to address in a recent AEON piece (https://aeon.co/essays/consciousness-is-not-a-thing-but-a-process-of-inference). What follows is based upon the notes for that essay, with a special focus on self-organization, self-evidencing and self-modeling. I will try to substantiate my (polemic) answer from the perspective of a physicist. In brief, the argument goes as follows: if we want to talk about creatures, like ourselves, then we have to identify the characteristic behaviors they must exhibit. This is fairly easy to do by noting that living systems return to a set of attracting states time and time again. Mathematically, this implies the existence of a Lyapunov function that turns out to be model evidence (i.e., self-evidence) in Bayesian statistics or surprise (i.e., self-information) in information theory. This means that all biological processes can be construed as performing some form of inference, from evolution through to conscious processing. If this is the case, at what point do we invoke consciousness? The proposal on offer here is that the mind comes into being when self-evidencing has a temporal thickness or counterfactual depth, which grounds inferences about the consequences of my action. On this view, consciousness is nothing more than inference about my future; namely, the self-evidencing consequences of what I could do.
There are many phenomena in the natural sciences that are predicated on the notion of “self”; namely, self-information, self-organization, self-assembly, self-evidencing, self-modeling, self-consciousness and self-awareness. To what extent does one entail the others? This essay tries to unpack the relationship among these phenomena from first (variational) principles. Its conclusion can be summarized as follows: living implies the existence of “lived” states that are frequented in a characteristic way. This mandates the optimization of a mathematical function called “surprise” (or self-information) in information theory and “evidence” in statistics. This means that biological processes can be construed as an inference process; from evolution through to conscious processing. So where does consciousness emerge? The proposal offered here is that conscious processing has a temporal thickness or depth, which underwrites inferences about the consequences of action.
