Tag Archives: neuron

Narrating neuroscience in Toronto (Canada) on Oct. 20, 2017 and knitting a neuron

What is it with the Canadian neuroscience community? First, there’s The Beautiful Brain an exhibition of the extraordinary drawings of Santiago Ramón y Cajal (1852–1934) at the Belkin Gallery on the University of British Columbia (UBC) campus in Vancouver and a series of events marking the exhibition (for more see my Sept. 11, 2017 posting ; scroll down about 30% for information about the drawings and the events still to come).

I guess there must be some money floating around for raising public awareness because now there’s a neuroscience and ‘storytelling’ event (Narrating Neuroscience) in Toronto, Canada. From a Sept. 25, 2017 ArtSci Salon announcement (received via email),

With NARRATING NEUROSCIENCE we plan to initiate a discussion on the  role and the use of storytelling and art (both in verbal and visual  forms) to communicate abstract and complex concepts in neuroscience to  very different audiences, ranging from fellow scientists, clinicians and patients, to social scientists and the general public. We invited four guests to share their research through case studies and experiences stemming directly from their research or from other practices they have adopted and incorporated into their research, where storytelling and the arts have played a crucial role not only in communicating cutting edge research in neuroscience, but also in developing and advancing it.

OUR GUESTS

MATTEO FARINELLA, PhD, Presidential Scholar in Society and Neuroscience – Columbia University

SHELLEY WALL , AOCAD, MSc, PhD – Assistant professor, Biomedical Communications Graduate Program and Department of Biology, UTM

ALFONSO FASANO, MD, PhD, Associate Professor – University of Toronto Clinician Investigator – Krembil Research Institute Movement Disorders Centre – Toronto Western Hospital

TAHANI BAAKDHAH, MD, MSc, PhD candidate – University of Toronto

DATE: October 20, 2017
TIME: 6:00-8:00 pm
LOCATION: The Fields Institute for Research in Mathematical Sciences
222 College Street, Toronto, ON

Events Facilitators: Roberta Buiani and Stephen Morris (ArtSci Salon) and Nina Czegledy (Leonardo Network)

TAHANI BAAKDHAH is a PhD student at the University of Toronto studying how the stem cells built our retina during development, the mechanism by which the light sensing cells inside the eye enable us to see this beautiful world and how we can regenerate these cells in case of disease or injury.

MATTEO FARINELLA combines a background in neuroscience with a lifelong passion for drawing, making comics and illustrations about the brain. He is the author of _Neurocomic_ (Nobrow 2013) published with the support of the Wellcome Trust, _Cervellopoli_ (Editoriale Scienza 2017) and he has collaborated with universities and educational institutions around
the world to make science more clear and accessible. In 2016 Matteo joined Columbia University as a Presidential Scholar in Society and Neuroscience, where he investigates the role of visual narratives in science communication. Working with science journalists, educators and cognitive neuroscientists he aims to understand how these tools may
affect the public perception of science and increase scientific literacy (cartoonscience.org [2]).

ALFONSO FASANO graduated from the Catholic University of Rome, Italy, in 2002 and became a neurologist in 2007. After a 2-year fellowship at the University of Kiel, Germany, he completed a PhD in neuroscience at the Catholic University of Rome. In 2013 he joined the Movement Disorder Centre at Toronto Western Hospital, where he is the co-director of the
surgical program for movement disorders. He is also an associate professor of medicine in the Division of Neurology at the University of Toronto and clinician investigator at the Krembil Research Institute. Dr. Fasano’s main areas of interest are the treatment of movement  disorders with advanced technology (infusion pumps and neuromodulation), pathophysiology and treatment of tremor and gait disorders. He is author of more than 170 papers and book chapters. He is principal investigator of several clinical trials.

SHELLEY WALL is an assistant professor in the University of Toronto’s Biomedical Communications graduate program, a certified medical illustrator, and inaugural Illustrator-in-Residence in the Faculty of Medicine, University of Toronto. One of her primary areas of research, teaching, and creation is graphic medicine—the intersection of comics with illness, medicine, and caregiving—and one of her ongoing projects is a series of comics about caregiving and young onset Parkinson’s disease.

You can register for this free Toronto event here.

One brief observation, there aren’t any writers (other than academics) or storytellers included in this ‘storytelling’ event. The ‘storytelling’ being featured is visual. To be blunt I’m not of the ‘one picture is worth a thousand words’ school of thinking (see my Feb. 22, 2011 posting). Yes, sometimes pictures are all you need but that tiresome aphorism which suggests  communication can be reduced to one means of communication really needs to be retired. As for academic writing, it’s not noted for its storytelling qualities or experimentation. Academics are not judged on their writing or storytelling skills although there are some who are very good.

Getting back to the Toronto event, they seem to have the visual part of their focus  ” … discussion on the  role and the use of storytelling and art (both in verbal and visual  forms) … ” covered. Having recently attended a somewhat similar event in Vancouver, which was announced n my Sept. 11, 2017 posting, there were some exciting images and ideas presented.

The ArtSci Salon folks also announced this (from the Sept. 25, 2017 ArtSci Salon announcement; received via email),

ATTENTION ARTSCI SALONISTAS AND FANS OF ART AND SCIENCE!!
CALL FOR KNITTING AND CROCHET LOVERS!

In addition to being a PhD student at the University of Toronto, Tahani Baakdhah is a prolific knitter and crocheter and has been the motor behind two successful Knit-a-Neuron Toronto initiatives. We invite all Knitters and Crocheters among our ArtSci Salonistas to pick a pattern
(link below) and knit a neuron (or 2! Or as many as you want!!)

http://bit.ly/2y05hRR

BRING THEM TO OUR OCTOBER 20 ARTSCI SALON!
Come to the ArtSci Salon and knit there!
You can’t come?
Share a picture with @ArtSci_Salon @SciCommTO #KnitANeuronTO [3] on
social media
Or…Drop us a line at artscisalon@gmail.com !

I think it’s been a few years since my last science knitting post. No, it was Oct. 18, 2016. Moving on, I found more neuron knitting while researching this piece. Here’s the Neural Knitworks group, which is part of Australia’s National Science Week (11-19 August 2018) initiative (from the Neural Knitworks webpage),

Neural Knitworks is a collaborative project about mind and brain health.

Whether you’re a whiz with yarn, or just discovering the joy of craft, now you can crochet wrap, knit or knot—and find out about neuroscience.

During 2014 an enormous number of handmade neurons were donated (1665 in total!) and used to build a giant walk-in brain, as seen here at Hazelhurst Gallery [scroll to end of this post]. Since then Neural Knitworks have been held in dozens of communities across Australia, with installations created in Queensland, the ACT, Singapore, as part of the Cambridge Science Festival in the UK and in Philadelphia, USA.

In 2017, the Neural Knitworks team again invites you to host your own home-grown Neural Knitwork for National Science Week*. Together we’ll create a giant ‘virtual’ neural network by linking your displays visually online.

* If you wish to host a Neural Knitwork event outside of National Science Week or internationally we ask that you contact us to seek permission to use the material, particularly if you intend to create derivative works or would like to exhibit the giant brain. Please outline your plans in an email.

Your creation can be big or small, part of a formal display, or simply consist of neighbourhood neuron ‘yarn-bombings’. Knitworks can be created at home, at work or at school. No knitting experience is required and all ages can participate.

See below for how to register your event and download our scientifically informed patterns.

What is a neuron?

Neurons are electrically excitable cells of the brain, spinal cord and peripheral nerves. The billions of neurons in your body connect to each other in neural networks. They receive signals from every sense, control movement, create memories, and form the neural basis of every thought.

Check out the neuron microscopy gallery for some real-world inspiration.

What happens at a Neural Knitwork?

Neural Knitworks are based on the principle that yarn craft, with its mental challenges, social connection and mindfulness, helps keep our brains and minds sharp, engaged and healthy.

Have fun as you

  • design your own woolly neurons, or get inspired by our scientifically-informed knitting, crochet or knot patterns;
  • natter with neuroscientists and teach them a few of your crafty tricks;
  • contribute to a travelling textile brain exhibition;
  • increase your attention span and test your memory.

Calm your mind and craft your own brain health as you

  • forge friendships;
  • solve creative and mental challenges;
  • practice mindfulness and relaxation;
  • teach and learn;
  • develop eye-hand coordination and fine motor dexterity.

Interested in hosting a Neural Knitwork?

  1. Log your event on the National Science Week calendar to take advantage of multi-channel promotion.
  2. Share the link^ for this Neural Knitwork page on your own website or online newsletter and add information your own event details.
  3. Use this flyer template (2.5 MB .docx) to promote your event in local shop windows and on noticeboards.
  4. Read our event organisers toolbox for tips on hosting a successful event.
  5. You’ll need plenty of yarn, needles, copies of our scientifically-based neuron crafting pattern books (3.4 MB PDF) and a comfy spot in which to create.
  6. Gather together a group of friends who knit, crochet, design, spin, weave and anyone keen to give it a go. Those who know how to knit can teach others how to do it, and there’s even an easy no knit pattern that you can knot.
  7. Download a neuroscience podcast to listen to, and you’ve got a Neural Knitwork!
  8. Join the Neural Knitworks community on Facebook  to share and find information about events including public talks featuring neuroscientists.
  9. Tweet #neuralknitworks to show us your creations.
  10. Find display ideas in the pattern book and on our Facebook page.

Finally,, the knitted neurons from Australia’s 2014 National Science Week brain exhibit,

[downloaded from https://www.scienceweek.net.au/neural-knitworks/]

Neuristors and brainlike computing

As you might suspect, a neuristor is based on a memristor .(For a description of a memristor there’s this Wikipedia entry and you can search this blog with the tags ‘memristor’ and neuromorphic engineering’ for more here.)

Being new to neuristors ,I needed a little more information before reading the latest and found this Dec. 24, 2012 article by John Timmer for Ars Technica (Note: Links have been removed),

Computing hardware is composed of a series of binary switches; they’re either on or off. The other piece of computational hardware we’re familiar with, the brain, doesn’t work anything like that. Rather than being on or off, individual neurons exhibit brief spikes of activity, and encode information in the pattern and timing of these spikes. The differences between the two have made it difficult to model neurons using computer hardware. In fact, the recent, successful generation of a flexible neural system required that each neuron be modeled separately in software in order to get the sort of spiking behavior real neurons display.

But researchers may have figured out a way to create a chip that spikes. The people at HP labs who have been working on memristors have figured out a combination of memristors and capacitors that can create a spiking output pattern. Although these spikes appear to be more regular than the ones produced by actual neurons, it might be possible to create versions that are a bit more variable than this one. And, more significantly, it should be possible to fabricate them in large numbers, possibly right on a silicon chip.

The key to making the devices is something called a Mott insulator. These are materials that would normally be able to conduct electricity, but are unable to because of interactions among their electrons. Critically, these interactions weaken with elevated temperatures. So, by heating a Mott insulator, it’s possible to turn it into a conductor. In the case of the material used here, NbO2, the heat is supplied by resistance itself. By applying a voltage to the NbO2 in the device, it becomes a resistor, heats up, and, when it reaches a critical temperature, turns into a conductor, allowing current to flow through. But, given the chance to cool off, the device will return to its resistive state. Formally, this behavior is described as a memristor.

To get the sort of spiking behavior seen in a neuron, the authors turned to a simplified model of neurons based on the proteins that allow them to transmit electrical signals. When a neuron fires, sodium channels open, allowing ions to rush into a nerve cell, and changing the relative charges inside and outside its membrane. In response to these changes, potassium channels then open, allowing different ions out, and restoring the charge balance. That shuts the whole thing down, and allows various pumps to start restoring the initial ion balance.

Here’s a link to and a citation for the research paper described in Timmer’s article,

A scalable neuristor built with Mott memristors by Matthew D. Pickett, Gilberto Medeiros-Ribeiro, & R. Stanley Williams. Nature Materials 12, 114–117 (2013) doi:10.1038/nmat3510 Published online 16 December 2012

This paper is behind a paywall.

A July 28, 2017 news item on Nanowerk provides an update on neuristors,

A future android brain like that of Star Trek’s Commander Data might contain neuristors, multi-circuit components that emulate the firings of human neurons.

Neuristors already exist today in labs, in small quantities, and to fuel the quest to boost neuristors’ power and numbers for practical use in brain-like computing, the U.S. Department of Defense has awarded a $7.1 million grant to a research team led by the Georgia Institute of Technology. The researchers will mainly work on new metal oxide materials that buzz electronically at the nanoscale to emulate the way human neural networks buzz with electric potential on a cellular level.

A July 28, 2017 Georgia Tech news release, which originated the news item, delves further into neuristors and the proposed work leading to an artificial retina that can learn (!). This was not where I was expecting things to go,

But let’s walk expectations back from the distant sci-fi future into the scientific present: The research team is developing its neuristor materials to build an intelligent light sensor, and not some artificial version of the human brain, which would require hundreds of trillions of circuits.

“We’re not going to reach circuit complexities of that magnitude, not even a tenth,” said Alan Doolittle, a professor at Georgia Tech’s School of Electrical and Computer Engineering. “Also, currently science doesn’t really know yet very well how the human brain works, so we can’t duplicate it.”

Intelligent retina

But an artificial retina that can learn autonomously appears well within reach of the research team from Georgia Tech and Binghamton University. Despite the term “retina,” the development is not intended as a medical implant, but it could be used in advanced image recognition cameras for national defense and police work.

At the same time, it would significantly advance brain-mimicking, or neuromorphic, computing. The research field that takes its cues from what science already does know about how the brain computes to develop exponentially more powerful computing.

The retina would be comprised of an array of ultra-compact circuits called neuristors (a word combining “neuron” and “transistor”) that sense light, compute an image out of it and store the image. All three of the functions would occur simultaneously and nearly instantaneously.

“The same device senses, computes and stores the image,” Doolittle said. “The device is the sensor, and it’s the processor, and it’s the memory all at the same time.” A neuristor itself is comprised in part of devices called memristors inspired by the way human neurons work.

Brain vs. PC

That cuts out loads of processing and memory lag time that are inherent in traditional computing.

Take the device you’re reading this article on: Its microprocessor has to tap a separate memory component to get data, then do some processing, tap memory again for more data, process some more, etc. “That back-and-forth from memory to microprocessor has created a bottleneck,” Doolittle said.

A neuristor array breaks the bottleneck by emulating the extreme flexibility of biological nervous systems: When a brain computes, it uses a broad set of neural pathways that flash with enormous data. Then, later, to compute the same thing again, it will use quite different neural paths.

Traditional computer pathways, by contrast, are hardwired. For example, look at a present-day processor and you’ll see lines etched into it. Those are pathways that computational signals are limited to.

The new memristor materials at the heart of the neuristor are not etched, and signals flow through the surface very freely, more like they do through the brain, exponentially increasing the number of possible pathways computation can take. That helps the new intelligent retina compute powerfully and swiftly.

Terrorists, missing children

The retina’s memory could also store thousands of photos, allowing it to immediately match up what it sees with the saved images. The retina could pinpoint known terror suspects in a crowd, find missing children, or identify enemy aircraft virtually instantaneously, without having to trawl databases to correctly identify what is in the images.

Even if you take away the optics, the new neuristor arrays still advance artificial intelligence. Instead of light, a surface of neuristors could absorb massive data streams at once, compute them, store them, and compare them to patterns of other data, immediately. It could even autonomously learn to extrapolate further information, like calculating the third dimension out of data from two dimensions.

“It will work with anything that has a repetitive pattern like radar signatures, for example,” Doolittle said. “Right now, that’s too challenging to compute, because radar information is flying out at such a high data rate that no computer can even think about keeping up.”

Smart materials

The research project’s title acronym CEREBRAL may hint at distant dreams of an artificial brain, but what it stands for spells out the present goal in neuromorphic computing: Cross-disciplinary Electronic-ionic Research Enabling Biologically Realistic Autonomous Learning.

The intelligent retina’s neuristors are based on novel metal oxide nanotechnology materials, unique to Georgia Tech. They allow computing signals to flow flexibly across pathways that are electronic, which is customary in computing, and at the same time make use of ion motion, which is more commonly know from the way batteries and biological systems work.

The new materials have already been created, and they work, but the researchers don’t yet fully understand why.

Much of the project is dedicated to examining quantum states in the materials and how those states help create useful electronic-ionic properties. Researchers will view them by bombarding the metal oxides with extremely bright x-ray photons at the recently constructed National Synchrotron Light Source II.

Grant sub-awardee Binghamton University is located close by, and Binghamton physicists will run experiments and hone them via theoretical modeling.

‘Sea of lithium’

The neuristors are created mainly by the way the metal oxide materials are grown in the lab, which has advantages over building neuristors in a more wired way.

This materials-growing approach is conducive to mass production. Also, though neuristors in general free signals to take multiple pathways, Georgia Tech’s neuristors do it much more flexibly thanks to chemical properties.

“We also have a sea of lithium, and it’s like an infinite reservoir of computational ionic fluid,” Doolittle said. The lithium niobite imitates the way ionic fluid bathes biological neurons and allows them to flash with electric potential while signaling. In a neuristor array, the lithium niobite helps computational signaling move in myriad directions.

“It’s not like the typical semiconductor material, where you etch a line, and only that line has the computational material,” Doolittle said.

Commander Data’s brain?

“Unlike any other previous neuristors, our neuristors will adapt themselves in their computational-electronic pulsing on the fly, which makes them more like a neurological system,” Doolittle said. “They mimic biology in that we have ion drift across the material to create the memristors (the memory part of neuristors).”

Brains are far superior to computers at most things, but not all. Brains recognize objects and do motor tasks much better. But computers are much better at arithmetic and data processing.

Neuristor arrays can meld both types of computing, making them biological and algorithmic at once, a bit like Commander Data’s brain.

The research is being funded through the U.S. Department of Defense’s Multidisciplinary University Research Initiatives (MURI) Program under grant number FOA: N00014-16-R-FO05. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of those agencies.

Fascinating, non?