Spectacular Visualizations of Brain Scans Enhanced with 1,750 Pieces of Gold Leaf

Self Reflected, 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The entire Self Reflected microetching under violet and white light. (photo by Greg Dunn and Will Drinker)

Anyone who thinks that scientists can't be artists need look no further than Dr. Greg Dunn and Dr. Brian Edwards. The neuroscientist and applied physicist have paired together to create an artistic series of images that the artists describe as “the most fundamental self-portrait ever created.” Literally going inside, the pair has blown up a thin slice of the brain 22 times in a series called Self-Reflected.

Traveling across 500,000 neurons, the images took two years to complete, as Dunn and Edwards developed special technology for the project. Using a technique they've called reflective microetching, they microscopically manipulated the reflectivity of the brain's surface. Different regions of the brain were hand painted and digitized, later using a computer program created by Edwards to show the complex choreography our mind undergoes as it processes information.

After printing the designs onto transparencies, the duo added 1,750 gold leaf sheets to increase the art's reflectivity. The astounding results are images that demonstrate the delicate flow and balance of our brain's activity. “Self Reflected was created to remind us that the most marvelous machine in the known universe is at the core of our being and is the root of our shared humanity,” the artists share.

Self Reflected fine art prints and microetchings are available for purchase via Dunn's website.

Self Reflected is an unprecedented look inside the brain.

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The parietal gyrus where movement and vision are integrated. (photo by Greg Dunn and Will Drinker)

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The brainstem and cerebellum, regions that control basic body and motor functions. (photo by Greg Dunn and Will Drinker)

An astounding achievement in scientific art, the artists applied 1,750 leaves of gold to the final microetchings.

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The laminar structure of the cerebellum, a region involved in movement and proprioception (calculating where your body is in space).

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The pons, a region involved in movement and implicated in consciousness. (photo by Greg Dunn and Will Drinker)

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. Raw colorized microetching data from the reticular formation.

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The visual cortex, the region located at the back of the brain that processes visual information.

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The thalamus and basal ganglia, sorting senses, initiating movement, and making decisions. (photo by Greg Dunn and Will Drinker)

Self Reflected, 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The entire Self Reflected microetching under white light. (photo by Greg Dunn and Will Drinker)

Self Reflected (detail), 22K gilded microetching, 96″ X 130″, 2014-2016, Greg Dunn and Brian Edwards. The midbrain, an area that carries out diverse functions in reward, eye movement, hearing, attention, and movement. (photo by Greg Dunn and Will Drinker)

This video shows how the etched neurons twinkle as a light source is moved.

Interested in learning more? Watch Dr. Greg Dunn present the project at The Franklin Institute.

Dr. Greg Dunn: Website | Facebook | Instagram

My Modern Met granted permission to use photos by Dr. Greg Dunn.

ORIGINAL: My MET
By Jessica Stewart 
April 12, 2017

A Visual History of Human Knowledge | Manuel Lima | TED Talks

How does knowledge grow? 

Source: EPFL Blue Brain Project. Blue Brain Circuit

Sometimes it begins with one insight and grows into many branches. Infographics expert Manuel Lima explores the thousand-year history of mapping data — from languages to dynasties — using trees of information. It's a fascinating history of visualizations, and a look into humanity's urge to map what we know.

ORIGINAL: TED

Sep 10, 2015

Fluorescent proteins light up science by making the invisible visible

Multiple fluorescent proteins illuminate the cells in a human brainstem. Jeff Lichtman/Harvard University, CC BY-NC-ND

When you look up at the blue sky, where are the stars that you see at night? They’re there but we can’t see them. A firefly flitting across a field is invisible to us during the day, but at night we can easily spot its flashes. Similarly, proteins, viruses, parasites and bacteria inside living cells can’t be seen by the naked eye under normal conditions. But a technique using a fluorescent protein can light up cells' molecular machinations like a microscopic flashlight.

The crystal jellyfish has about 300 photo organs on the bottom edge of the jellyfish’s umbrella.Courtesy Steven Haddock – http://biolum.eemb.ucsb.edu, Author provided

The first fluorescent protein found in nature comes from the crystal jellyfish, Aequorea victoria, where it is responsible for the green light emitted by its photo organs. It’s called green fluorescent protein (GFP). We don’t know why these jellyfish have this lit-up feature.

Fluorescent proteins absorb light with short wavelengths, such as blue light, and immediately return it with a different color light that has a longer wavelength, such as green. In Aequorea victoria, a protein named aequorin produces blue light which GFP converts into the green light emitted by the jellyfish’s photo organs. This visibility under standard conditions is extremely rare; most other organisms have fluorescent proteins that are only visible if they are illuminated by external blue light sources.

Close up of a few of the photo organs. Courtesy Steven Haddock – http://biolum.eemb.ucsb.edu,Author provided

After the green fluorescent jellyfish protein, many other fluorescent proteins have been both found in nature and created in the lab. We now have a spectrum of fluorescent colors available to us that make previously invisible biological structures and processes visible in blazing fluorescent glory. Many new applications reliant on these colors are being published on a regular basis.

Petri dish with bacterial colonies expressing differently colored fluorescent proteins. These fluorescent proteins developed by Roger Tsien’s group are called the mFruits and have names like mHoneydew, mTomato, mCherry, mRaspberry, and mPlum. Paul Steinbach and Roger Y. Tsien, University of California, San Diego, CC BY-SA

Shining a light on imaging

Fluorescent protein technology has led to many other interesting developments designed to improve imaging with these glowing molecules.

CaMPARI is one new technique, short for calcium-modulated photoactivatable ratiometric integrator. By exploiting the fact that calcium concentrations change when nerve cells send signals, CaMPARI is able to light up all the neurons that have fired in a living organism. The technique is based on a fluorescent protein called EOS, which changes its fluorescence from green to red. In fruit flies, zebrafish and mice, CaMPARI-genetically-modified neurons fluoresce red if they are active and green if they are less active.

CaMPARI fluorescence in a larval zebrafish brain showing active neurons (magenta) that were marked while the fish was swimming freely. Looger Lab (HHMI/Janelia), Science, VOL 347, ISSUE 6223.

Before CaMPARI, all the fluorescent calcium indicators available temporarily lit up when the neuron fired. They couldn’t record the firing history of neurons or indicate whether a neuron had fired in the past. According to Loren Looger, one of the researchers who worked on the development of CaMPARI, “The most enabling thing about this technology may be that you don’t have to have your organism under a microscope during your experiment. So we can now visualize neural activity in fly larvae crawling on a plate or fish swimming in a dish.”

The CLARITY technique removes opaque parts and makes the whole brain transparent.

Expanding and transparent brains

Even with the help of light emitted by fluorescent proteins, it’s difficult to image neurons tangled deep within the brain. Ed Boyden, a neuroscientist from MIT, has created a method to expand brains to make fluorescent neurons deep within the brain more visible. He uses acrylate, which forms a dense mesh to hold the brain in place and expand in the presence of water thereby inflating the brain equally by about 4.5 times in each direction. It’s a lot like a diaper expanding when it gets wet. Boyden thinks that this “expansion microscopy may provide a key tool for comprehensive, precise, circuit-wide, brain mapping.”

Intact adult mouse brain before and after the CLARITY process. The Deisseroth Lab

One of the reasons expansion microscopy is so useful is that the brain can be made see-through before it is blown up several sizes larger. In 2013 Karl Deisseroth and Viviana Gradinaru at Stanford published a method called CLARITY that removes opaque molecules such as fats and makes the brain transparent without changing its shape. According to Thomas Insel, director of the US National Institute of Mental Health, “This is probably one of the most important advances for doing neuroanatomy in decades.” Since developing CLARITY for brains, Gradinaru has extended the method to all other organs including an entire mouse.

Both of these methods can be applied to brains that have been genetically modified with fluorescent proteins, therefore allowing for the visualization of neurons deep within the brain.

Mouse neurons labeled by GFPs. Wellcome Images, CC BY-NC-ND

In 2008, the three scientists responsible for taking GFP from the jellyfish and making it a common tool used in over a million experiments all over the world were awarded the 100th Nobel Prize in chemistry. And in 2014 three other scientists were awarded the Nobel Prize for using fluorescent protein to increase the resolution of light microscopes.

E. coli with GFPs glowing in their petri dishes. Carlos de Paz, CC BY-NC-SA

Revolutionary and resilient

I’ve been researching the photochemistry and photophysics of fluorescent proteins since they were first used in imaging technology in 1994, I’ve written two books on them, and still I’m stunned by the many different ways in which this fairly simple protein can be used. Perhaps I shouldn’t be surprised that plasmid DNA molecules coding for GFP have survived space flight – not inside the rocket, but on the outside where they were exposed to 1800F (1000C) temperatures and mad friction. 53% of the DNA intentionally placed inside the screw heads in the TEXUS-49 rocket mission expressed fully fluorescent GFP when inserted into cells upon return to earth.

Like stars at night, fluorescent proteins have been lighting up science for the last 20 years. And it won’t be long before they’re guiding surgeons to tumorous growths during surgery and allowing researchers to switch on and off selected biomolecular processes.

ORIGINAL: The Conversation

By Marc Zimmer. Professor of Chemistry and Dean of Studies at Connecticut College

April 7 2015, 6.16am EDT

DISCLOSURE STATEMENT. Marc Zimmer receives funding from NIH.

The Conversation is funded by Gordon and Betty Moore Foundation, Howard Hughes Medical Institute, Robert Wood Johnson Foundation, Alfred P Sloan Foundation and William and Flora Hewlett Foundation. Our global publishing platform is funded by Commonwealth Bank of Australia.

MIT Media Lab’s Kevin Hu wants to turn the invisible visible

MIT Media Lab’s Kevin Hu wants to turn the invisible visible

Big Data, HCI, Media Lab, MIT, Visualization, 

Photo by Alan Savenor 

Last March, MIT Media Lab Grad student Kevin Hu and his colleague Amy Yu saw their Pantheon project land on the front cover of The New York Times Magazine. Not bad for two grad students who are part of a generation using today’s seemingly unlimited technological innovations to change the world.

Focused on human data interfaces, Hu and his colleagues at the MIT Media Lab are part of the Macro Connections Group led by Cesar A. Hildago, where their sole mantra is “transform data into knowledge.” One of his current projects, DIVE, automatically generates Web-based, interactive visualizations of structured data sets.

What I discovered when I sat down with Kevin is that all those maps we now explore as click-bait on BuzzFeed, The Atlantic, and The Week explaining everything from the conflict in the Middle East to which states are more adulterous, are only going to become more ubiquitous if Kevin gets his way.

“DIVE is a way to turn the invisible, visible. We want to democratize data visualization so that anyone with data can map an image that explains things,” said Hu. His goal is to remove the middlemen who interpret data for us.

But he and his classmates also want to know more about human emotions with another project called Quantify. They want a computer that, or should we say “who,” can feel out the squishy stuff. Can emotions be data? When Hu and fellow lab student, Travis Rich (also his roommate, is there any other way when you are 20-something?) invented Gif Gif, the theory of Quantify took shape. I sat down with Kevin to learn how he plans to change the way we live and digest information.

What happened with Pantheon after the NY Times Magazine cover?

When the cover hit, we got a lot of attention. We had a couple hundred thousand page views. Amy Yu led the project and I joined. We ran into a lot of controversy because people, and The New York Times, focused on the rankings rather than our goal of cultural production over time. We were less interested if a celebrity were number five or six but rather the aggregate: How many physicists have changed over time, what is our country’s cultural composition? Instead we had angry e-mails from Canadians asking why Avril Lavigne was above Frank Gehry.

The real point of the project was to see cultural production and how it changes over time. We think of cultural production, in the broadest sense, as information that’s transmitted by nongenetic means, like what we’re doing right now. Anything that’s not encoded in our DNA: The shoes we wear, the coffee we drink, and the language we speak. We consider that all to be culture and we proxy it by people.

What’s on your desk today?

DIVE. It’s trying to make data visualization accessible. It’s trying to democratize the use of data visualization, like the charts you see in The New York Times. One of the real powers of Pantheon was that anyone could look at this tree map or scatter plot or diagram and understand the story being told. The trouble is it takes a long time to build this tool. The New York Times has great interactive visualizations but they have a whole team dedicated to it.

DIVE is a way that people can automatically build visualizations, allowing a journalist to easily imbed a data-driven graphic, or an educator or researcher to easily build a visual tool.

How would you define the challenge of data visualization?

The fundamental problem is that we’re trying to translate between three worlds: 

• The world of information: Bits; 
• The world of knowledge: Neurons and cells; and 
• the world of visualization: Pixels. 

Until we all are cyborgs and can plug in this data and automatically get what we need, we will need pixels. Data visualization is entirely concerned with how we represent these bits in terms of pixels on a 2-D screen. How do we turn the invisible to the visible?

What drew you to explore macro-connections?

I was studying physics but I was kind of frustrated with the current research scope of physics. It seems to me that people are concerned with either what’s very big (cosmology and astrophysics), or very small (high energy physics). But I was interested in learning how to understand everyday phenomena.

I was interested in looking at people who are applying physics to social problems and to things that we do not understand such as organizational structures, social dynamics, and the spread of epidemics.

What do you see that we don’t? How do you apply physics to social structures and problems?

I think it’s mostly a cultural thing. For the longest time social sciences could only tell us how we can think about a problem, not how we can actually solve it. But now we actually have the data to solve the problem. That’s very frightening but it’s very powerful and it’s a very new phenomenon.

Ten years ago, we didn’t have the data to create things like Pantheon. Now we have Facebook and OK Cupid that have great data logs. For the first time, we have actual data about self-identity. We now have how we view ourselves and how we view others. Physics is all about modeling these phenomena.

So these ‘squishy’ social things start to seem more linear?

Yes, exactly. Exactly.

How will DIVE change our lives? And can you already see it taking place?

I can. Imagine if journalists could use data visualization in their articles. Imagine if consultants could use it. The pipe dream is that in the future we have a completely data-literate society where when we talk about policies or about disaster relief, we have real-time, high-resolution, clean data sets and anybody has the ability to think about social issues rigorously.

For many issues, we see them through another person’s interpretation. A great deal of science reporting, for instance, is very second and third hand. Very few people actually read the research paper. Data visualization allows everyone to understand issues. DIVE is trying to close that gap such that when we acquire information about the world, we can get it first hand and we can mine it ourselves.

You sent me a test called Place Pulse before this interview. Why? 

Travis and I had this vision that we want to give computers the capability to reason about objects the way that we do. When computers think of gifs, they think of bits. When we think of gifs or videos, we think of their content. We may think of this video as being very emotionally compelling or this picture being very angry. That’s how we may think of an image but that’s not how a computer does.

Are you’re trying to give the computer emotions?

Yes, to give it the capability to think of media emotionally. It can reason very well, better than humans for anything that’s very computational and linear. But when we try to attach emotional intelligence to computers, we are not yet there. A computer cannot yet measure that this atrium is very clean, but a human can. We need a human in the loop.

We’ve built this comparison tool off the Quantify platform. You can imagine a whole list of comparable media that we can better measure if only we had the tools. How useful would it be if you could search Netflix this way? Or compare articles of clothing and know which one looks better on you or which one is more acceptable? Or compare experiences and know which one is more painful? Quantify allows this.

How do you convince people to give you that data?

We made it fun. Travis and I also built Gif Gif last March and it inspired Quantify. We have two million votes already. People like viewing gifs and contributing to knowledge but furthermore, we can give you a sense of what you like. What is your emotional profile? How did you vote in comparison to others? That makes it more interesting to share.

Who uses Gif Gif now?

People from all over the world use it. I’d say that the demographics are probably mostly teenagers because, really, who’s voting on gifs at 2 p.m. on Tuesday?

There is also a display in the lab called Mirror Mirror linked to Gif Gif. It’s a mirror with a webcam that uses facial recognition to measure emotions and it gives you back a gif. People love it and we didn’t expect people to love it, but it turns out that five-year-old children touring the lab and 60-year-old executives are all in front of it trying to say hi or trying to be angry.

What public opinion would you like to change?

I’d like to change the public’s opinion about experimentation. Human experimentation is an incredibly loaded term, for many very good reasons, and when Facebook said that they were experimenting with people’s newsfeeds, there was outrage. I think it’s kind of absurd. This is how software companies make tools. They test on their users and provide a service for free, and in exchange they use your data set. Clearly, if they give it to the wrong people, there’s potential for evil and abuse. I would like to see people be open and accepting of the fact that by contributing a little bit of anonymous information, they can help scientists better understand bigger issues like information flow, social network formation. I think that that should definitely change.

Why is the Media Lab so illustrious?

What I really look forward to every morning is the conversations I have with the people here in the lab. Gif Gif and Pantheon and DIVE – all those ideas really merged organically and there’s no real source: they all kind of came from the network and from conversations. A lot of people imagine people at the lab as people off in the air dreaming about what the next big thing will be, but really it’s just regular people having conversations and they happen to be asking, ‘what could be impactful?’ We’re aiming towards more paradigm shifts than incremental research. Is this going to be a game changer? Most of the time, the answer is ‘no,’ by definition, but it’s nice to be in a place where that is one of the first questions.

How do you keep going when things get tough on a project?

I’m taking this class at the lab called Tools For Wellbeing, as there’s a big initiative here about wellbeing, especially since MIT isn’t doing so well in that category. Pattie Maes actually teaches it sometimes. Last week’s subject was reframing. How do I reframe the situation? My answer to your question would definitely be to reframe it. Let’s say I’m trying to make this product but a feature isn’t working out. Well, one, can we design around that? Two, can we make do without it?

You dropped out of high school to go to Simon’s Rock School. How was that for you?

Simon’s Rock was probably the most formative two years of my life. It’s 300 kids in the Berkshires in the middle of nowhere in a pretty high-stress academic environment. It was very formative for me and I would do it again, but I don’t know if I’d enjoy it that much.

It’s considered an ‘early college.’ When I transferred to MIT from there, they accepted most of my Simon’s Rock credits.

Where do you get your news?

My media diet is 

• one third Twitter and Facebook, 
• one third very specific news sites that I like such as The New Yorker, New York Times, Huffington Post – the classic ones – The Economist – that sort of stuff – and 
• then one third Reddit.

What event are you looking forward to?

I’m looking forward to the MIT Media Lab’s Spring Members’ Meeting, which is sometime in April. During this meeting, lab sponsors (companies) come by for three days for research demos and updates. I’d love to get member’s feedback on DIVE, FOLD, and QUANTIFY when they’re further along, since outsiders are always candid with their comments and needs.

Secret source?

It’s a lame answer but McDonald’s. I’m a huge McDonald’s fan.

What do you order?

Fries and McFlurry. I grew up with McDonald’s and Lunchables. I try to eat healthier now but that’s definitely my go to. I go there at least twice a week.

That stuff’s poison!

It’s true but it’s too good.

Heidi Legg interviews visionaries and thinkers around us at TheEditorial.com Follow Heidi on Twitter - Facebook

ORIGINAL: Beta Boston

By Heidi Legg