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‘Minimalist machine learning’ algorithm analyzes complex microscopy and other images from very little data

Key tool for Chan-Zuckerberg-sponsored Human Cell Atlas project
March 16, 2018

These are images of a slice of mouse lymphblastoid cells; a. is the raw data, b is the corresponding manual segmentation and c is the output of an MS-D network with 100 layers. (credit: Data from A. Ekman and C. Larabell, National Center for X-ray Tomography.)

Mathematicians at Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a radical new approach to machine learning: a new type of highly efficient “deep convolutional neural network” that can automatically analyze complex experimental scientific images from limited data.*

As experimental facilities generate higher-resolution images at higher speeds, scientists struggle to manage and analyze the resulting data, which is often done painstakingly by hand.

For example, biologists record cell… read more

Neuroscientists devise scheme for mind-uploading centuries in the future

March 14, 2018

Representative electron micrograph of white matter region in cryopreserved pig brain (credit: Brain Preservation Foundation)

Two researchers — Robert McIntyre, an MIT graduate, and Gregory M. Fahy, PhD., 21st Century Medicine (21CM) Chief Scientific Officer, have developed a method for scanning a preserved brain’s connectome (the 150 trillion microscopic synaptic connections presumed to encode all of a person’s knowledge).

That data could possibly be used, centuries later, to reconstruct a whole-brain emulation — uploading your mind into a computer… read more

A high-density, stretchable, 32-electrode grid for neural recording and neurological disorder treatment

A potential Neuralink device? (see SXSW video)
March 12, 2018

Photo of a new soft, elastic, high-density 32-electrode grid for long-term, stable neural recording and treatment of neurological disorders. It’s based on a novel elastic material that's biocompatible and retains high electrical conductivity, even when stretched to double its original length. The 32 electrodes shown here are each 50 micrometers wide and located at a distance of 200 micrometers from each other. The fabrication procedure allows 32 electrodes to be placed onto a very small surface. The electrode grid is 3.2 millimeters wide and 80 micrometers thick. (credit: Thor Balkhed)

An international team has developed a soft, elastic, high-density stretchable electrode grid for long-term, stable neural recording, and diagnosis and treatment of neurological disorders, such as epilepsy.

Researchers at Linköping University and ETH Zürich developed the biocompatible, soft-material composite, which avoids the usual damage and inflammation to neurons from rigid metallic electrodes and components.

The material consists of gold coated titanium dioxide nanowires embedded… read more

Super-resolution microscopy captures images in both space and time

High-speed “4D” views inside living cells
March 9, 2018

Cell image using color-coded depth

Scientists at the Laboratory of Biomedical Optics (LOB) at EPFL (École Polytechnique Fédérale de Lausanne) in Switzerland have developed the first microscope platform that can perform “super-resolution” imaging in both space and time — capturing unprecedented “4D” views inside living cells. The landmark paper is published in Nature Photonics and on open-access ArXiv.

Super-resolution microscopy is a technique (covered extensively onread more

Metalens with artificial muscle simulates (and goes way beyond) human-eye and camera optical functions

Thin, flat structure promises to revolutionize eyeglasses, cameras, microscopes, and augmented and virtual-reality optics
March 2, 2018

A metalens (made of silicon) mounted on a transparent, stretchy polymer film, without any electrodes. The colorful iridescence is produced by the large number of nanostructures within the metalens. (credit:Harvard SEAS)

Researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a breakthrough electronically controlled artificial eye. The thin, flat, adaptive silicon nanostructure (“metalens”) can simultaneously control focus, astigmatism, and image shift (three of the major contributors to blurry images) in real time, which the human eye (and eyeglasses) cannot do.

The 30-micrometers-thick metalens makes changes laterally to achieve optical zoom, autofocus, and… read more

Measuring deep-brain neurons’ electrical signals at high speed with light instead of electrodes

“We will be able to watch a neural computation happen ... a step toward understanding what a thought or a feeling actually is.” --- Prof. Edward Boyden
February 28, 2018

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Researchers at MIT have developed a new approach to measure electrical activity deep in the brain: using light — an easier, faster, and more informative method than inserting electrodes.

They’ve developed a new light-sensitive protein that can be embedded into neuron membranes, where it emits a fluorescent signal that indicates how much voltage a particular cell is experiencing. This could allow scientists to study how neurons behave, millisecond… read more

Low-cost EEG can now be used to reconstruct images of what you see

Has promising uses for locked-in patients and forensics --- no expensive fMRI machine needed
February 27, 2018

(left) Test image. (right) Brain's image captured by EEG and decoded. (credit: Dan Nemrodov et al./eNeuro

A new technique developed by University of Toronto Scarborough neuroscientists has, for the first time, used EEG detection of brain activity in reconstructing images of what people perceive.

The new technique “could provide a means of communication for people who are unable to verbally communicate,” said Dan Nemrodov, Ph.D., a postdoctoral fellow in Assistant Professor Adrian Nestor’s lab at U of T Scarborough. “It could also have… read more

Do our brains use the same kind of deep-learning algorithms used in AI?

Bridging the gap between neuroscience and AI
February 23, 2018

This is an illustration of a multi-compartment neural network model for deep learning. Left: Reconstruction of pyramidal neurons from mouse primary visual cortex. Right: Illustration of simplified pyramidal neuron models. (credit: CIFAR)

Deep-learning researchers have found that certain neurons in the brain have shape and electrical properties that appear to be well-suited for “deep learning” — the kind of machine-intelligence used in beating humans at Go and Chess.

Canadian Institute For Advanced Research (CIFAR) Fellow Blake Richards and his colleagues — Jordan Guerguiev at the University of Toronto, Scarborough, and Timothy Lillicrap at Google DeepMind —… read more

Two new wearable sensors may replace traditional medical diagnostic devices

Breakthrough technologies presented at AAAS annual meeting Feb. 17, 2018
February 21, 2018

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Throat-motion sensor monitors stroke effects more effectively

A radical new type of stretchable, wearable sensor that measures vocal-cord movements could be a “game changer” for stroke rehabilitation, according to Northwestern University scientists. The sensors can also measure swallowing ability (which may be affected by stroke), heart function, muscle activity, and sleep quality. Developed in the lab of engineering professor John A.

read more

Neuroscientists reverse Alzheimer’s disease in mice

February 19, 2018

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Researchers from the Cleveland Clinic Lerner Research Institute have completely reversed the formation of amyloid plaques in the brains of mice with Alzheimer’s disease by gradually depleting an enzyme called BACE1. The procedure also improved the animals’ cognitive function.

The study, published February 14 in the Journal of Experimental Medicine, raises hopes that drugs targeting this enzyme will be able to successfully treat Alzheimer’s disease in… read more

How to train a robot to do complex abstract thinking

February 16, 2018

Robot inspects cooler, ponders next step (credit: Intelligent Robot Lab / Brown University)

Robots are great at following programmed steps. But asking a robot to “move the green bottle from the cooler to the cupboard” would require it to have abstract representations of these things and actions, plus knowledge of its surroundings.

(“Hmm, which of those millions of pixels is a ‘cooler,’ whatever than means? How do I get inside it and also the ‘cupboard’? …”)

To help robots answer these… read more

Ray Kurzweil’s ‘singularity’ prediction supported by prominent AI scientists

February 14, 2018

BrainAIPhoto

According to an article in web magazine Futurism today, two prominent artificial intelligence (AI) experts have agreed with inventor, author and futurist Ray Kurzweil’s prediction of singularity — a future period during which the pace of technological change will be so rapid, its impact so deep, that human life will be irreversibly transformed — to happen in about 30 years: Massachusetts Institute of… read more

Are you a cyborg?

How to generate electricity from your body, bioprint a brain, and “resleeve your stack.”
February 14, 2018

Vertebral chip (credit: Netflix)

Bioprinting a brain

A new bioprinting technique combines cryogenics (freezing) and 3D printing to create geometrical structures that are as soft (and complex) as the most delicate body tissues — mimicking the mechanical properties of organs such as the brain and lungs.

The idea: “Seed” porous scaffolds that can act as a template for tissue regeneration (from neuronal cells, for example), where damaged tissues are encouraged… read more

How to shine light deeper into the brain

Less-invasive way to stimulate the brain with light may lead to new treatments for neurological disorders
February 12, 2018

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An international team of researchers has developed a way to shine light at new depths in the brain. It may lead to development of new, non-invasive clinical treatments for neurological disorders and new research tools.

The new method extends the depth that optogenetics — a method for stimulating neurons with light — can reach. With optogenetics, blue-green light is used to turn on “light-gated ion channels” in neurons to stimulate… read more

AI algorithm with ‘social skills’ teaches humans how to collaborate

And a human-machine collaborative chatbot system
February 9, 2018

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An international team has developed an AI algorithm with social skills that has outperformed humans in the ability to cooperate with people and machines in playing a variety of two-player games.

The researchers, led by Iyad Rahwan, PhD, an MIT Associate Professor of Media Arts and Sciences, tested humans and the algorithm, called S# (“S sharp”), in three types of interactions: machine-machine, human-machine, and human-human. In most instances, machines programmed with… read more

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