Lifeboat Foundation

The Brain Preservation Foundation (BPF) announced that the Small Mammal Brain Preservation Prize has officially been won. The spectacular result achieved by 21st Century Medicine researchers provides the first demonstration that near-perfect, long-term structural preservation of an intact mammalian brain is achievable.

A team from 21st Century Medicine, spearheaded by recent MIT graduate Robert McIntyre, has discovered a way to preserve the delicate neural circuits of an intact rabbit brain for very long-term storage using a combination of chemical fixation and cryogenic cooling. Proof of this accomplishment, and the full “Aldehyde-Stabilized Cryopreservation” (ASC) protocol, was recently published in the journal Cryobiology and has been independently verified by the BPF through extensive electron microscopic examination conducted by the two official judges of the prize: BPF President Ken Hayworth and Princeton neuroscience professor Sebastian Seung, author of “Connectome: How the Brain’s Wiring Makes Us Who We Are.”

“Every neuron and synapse looks beautifully preserved across the entire brain,” said Hayworth. “Simply amazing given that I held in my hand this very same brain when it was frozen solid… This is not your father’s cryonics.”

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The US military is looking for ways to insert microscopic devices into human brains to help folks communicate with machines, like prosthetic limbs, with their minds. And now, DARPA’s saying scientists have found a way to do just that—without ripping open patients’ skulls.

In the DARPA-funded study, researchers at the University of Melbourne have developed a device that could help people use their brains to control machines. These machines might include technology that helps patients control physical disabilities or neurological disorders. The results were published in the journal Nature Biotechnology.

In the study, the team inserted a paperclip-sized object into the motor cortexes of sheep. (That’s the part of the brain that oversees voluntary movement.) The device is a twist on traditional stents, those teeny tiny tubes that surgeons stick in vessels to improve blood flow.

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Stanford University PhD candidate, Song Han, who works under advisor and networking pioneer, Dr. Bill Dally, responded in a most soft-spoken and thoughtful way to the question of whether the coupled software and hardware architecture he developed might change the world.

In fact, instead of answering the question directly, he pointed to the range of applications, both in the present and future, that will be driven by near real-time inference for complex deep neural networks—all a roundabout way of showing not just why what he is working toward is revolutionary, but why the missing pieces he is filling in have kept neural network-fed services at a relative constant.

There is one large barrier to that future Han considers imminent—one pushed by an existing range of neural network-driven applications powering all aspects of the consumer economy and, over time, the enterprise. And it’s less broadly technical than it is efficiency-driven. After all, considering the mode of service delivery of these applications, often lightweight, power-aware devices, how much computation can be effectively packed into the memory of such devices—and at what cost to battery life or overall power? Devices aside, these same concerns, at a grander level of scale, are even more pertinent at the datacenter where some bulk of the inference is handled.

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What if computers could recognize objects as well as the human brain could? Electrical engineers at the University of California, San Diego have taken an important step toward that goal by developing a pedestrian detection system that performs in near real-time (2−4 frames per second) and with higher accuracy (close to half the error) compared to existing systems. The technology, which incorporates deep learning models, could be used in “smart” vehicles, robotics and image and video search systems.

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A DARPA-funded research team has created a novel neural-recording device that can be implanted into the brain through blood vessels, reducing the need for invasive surgery and the risks associated with breaching the blood-brain barrier. The technology was developed under DARPA’s Reliable Neural-Interface Technology (RE-NET) program, and offers new potential for safely expanding the use of brain-machine interfaces (BMIs) to treat physical disabilities and neurological disorders.

In an article published in Nature Biotechnology, researchers in the Vascular Bionics Laboratory at the University of Melbourne led by neurologist Thomas Oxley, M.D., describe proof-of-concept results from a study conducted in sheep that demonstrate high-fidelity measurements taken from the motor cortex—the region of the brain responsible for controlling voluntary movement—using a novel device the size of a small paperclip.

This new device, which Oxley’s team dubbed the “stentrode,” was adapted from off-the-shelf stent technology—a familiar therapeutic tool for clearing and repairing blood vessels—to include an array of electrodes. The researchers also addressed the dual challenge of making the device flexible enough to safely pass through curving blood vessels, yet stiff enough that the array can emerge from the delivery tube at its destination.

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Australian scientists hope that a tiny device just 3cm long and a few millimetres wide will enable paralysed patients to walk again by allowing them to control bionic limbs with the power of subconscious thought.

The new device, dubbed the “bionic spine”, is the size of a small paperclip and will be implanted in three patients at the Royal Melbourne hospital in Victoria next year. The participants will be selected from the Austin Health spinal cord unit, and will be the first humans to trial the device, which so far has only been tested in sheep.

Doctors will make a tiny cut in the neck of the patients and feed a catheter containing the bionic spine up through the blood vessels leading into the brain, until it rests on top of the motor cortex, the part of the brain where nerve impulses that initiate voluntary muscle movements come from. The catheter will then be removed, leaving the bionic spine behind.

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Have you ever walked into a room and forgot why you where there? Or while in the middle of conversation forgot a person’s name? Or briefing your boss on a project, only to stumble because a crucial factoid escaped your mind?

Yeah, me too.

“Tip of the tongue” syndrome haunts us all — that feeling where you’re close to remembering something, but just can’t seem to get there. But what if, at that exact moment, an AI-powered “cognitive assistant” pitches in and delivers that missing piece of information straight into your ear?

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Carnegie Mellon University is embarking on a five-year, $12 million research effort to reverse-engineer the brain and “make computers think more like humans,” funded by the U.S. Intelligence Advanced Research Projects Activity (IARPA). The research is led by Tai Sing Lee, a professor in the Computer Science Department and the Center for the Neural Basis of Cognition (CNBC).

The research effort, through IARPA’s Machine Intelligence from Cortical Networks (MICrONS) research program, is part of the U.S. BRAIN Initiative to revolutionize the understanding of the human brain.

Continue reading “CMU announces research project to reverse-engineer brain algorithms, funded by IARPA” »

(Facebook) The above passage, written in a combination of letters and numbers, has been circulating social media for years and purports that only certain “strong minds” can read it.

That’s not exactly true — just about everybody can read the message with ease. But according to one scientist, our ability to read such messages reveals something pretty incredible about the brain.

Interpreting passages like this hardly activates the section of the brain associated with numbers, Jon Andoni Duñabeitia, part of a team of Spanish cognitive scientists who wrote five papers on the subject, told Business Insider. Instead, our brain knows to treat them like letters based on their similar appearance.

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