Category: Brain imaging

Lessons from sarcasm (so useful…)

The New York Times ran a story on brain imaging studies of sarcasm, The Science of Sarcasm (Not That You Care), by Dan Hurley. That’s right — that favourite rhetorical tool of the snarky adolescent has been subjected to brain imaging studies. The Pearson Assessment video — of an actor delivering the same lines twice, once sincerely, and once dripping sarcasm — is fun. I found myself thinking that I could have been MORE sarcastic.

Hurley, the author of the NYTimes article, does a pretty good job of explaining things, although I think that the idea that perceiving sarcasm requires a ‘theory of mind,’ alluded to in the article, is a bit of a problem — but I have that issue with a lot of the ‘theory of mind’ material because I think it ‘over-cognizes’ social perception (that’s my own issue, so I won’t dwell on it). Hurley discusses the research of Katherine P. Rankin, using MRI scans and the Awareness of Social Inference Test, or Tasit. I have looked on the website for the Memory and Aging Center of UCSF, and through PubMed and EurekAlert, but I can’t find the original report on this research (please post a comment if you know where it is).

“I was testing people’s ability to detect sarcasm based entirely on paralinguistic cues, the manner of expression,” Dr. Rankin said. What seems particularly interesting is that the part of the brain which seemed to be linked to sarcasm — damage to it by dementia impeded the ability to recognize sarcasm — was in the right hemisphere, not usually associated with language or social interaction (which are generally associated with the left hemisphere). Instead, sarcasm seemed to require activity in ‘a part of the right hemisphere previously identified as important only to detecting contextual background changes in visual tests.’

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Wired on imaging ‘neurohype’

Wired magazine has a good piece on recent attempts to market neuroimaging services to individual consumers, Brain Scans as Mind Readers? Don’t Believe the Hype, by psychiatrist Daniel Carlat. Vaughan at Mind Hacks has a good discussion of the piece, Don’t believe the neurohype (thanks to Vaughan, also, for alerting me to the original piece). The Wired article, in addition to sharing Carlat’s adventures with the pay-per-scan industry, has a nice table of ‘neurologisms’ as well to help out the less-neurohip among us (myself included).

(I was a bit chastened by the line: ‘Add the prefix neuro to a discipline and you get a new field with instant cred. But the science can be less than compelling.’ uhhh… we at Neuroanthropology hope that our readers will judge us by our results; we plan to earn our ‘cred.’)

As Vaughan discusses, some people have a financial interest in over-interpreting brain scans and exaggerating what they can do:

Scientists and responsible clinicians will know about these shortcomings and make sure they don’t oversell their findings, but commercial companies are not selling you the data, they’re selling you a way of make you feel better about your insecurities, whether they be commercial concerns or health worries.

All I would add to this is ‘most‘ scientists know about these shortcoming and don’t paper over them when describing their research (and we’re happy to heap scorn on those who don’t have the proper humility).

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Understanding Brain Imaging


By Chris Dudley, Matt Gasperetti, Mikey Narvaez, and Sarah Walorski

Do you remember the anti-drug public service announcement from the 1980s that showed an egg frying in a hot pan which represented your brain on drugs?

During the 1990s, brain imaging moved beyond fried eggs as computer technology allowed researchers to process large amounts of data required for functional imaging approaches. As a result, the PSA mentioned above no longer provides the most accurate analogy illustrating what happens to the brain when exposed to drugs.

Today, brain imaging research has helped create a sophisticated “disease model” of chemical dependence related to changes in the function of neurotransmitters and receptors in the brain. These circuits are responsible for reward processing, memory and learning, motivation and drive, in addition to control (Nora Volkow describes these circuits in a 2004 literature review).

This particular post focuses on the techniques used most commonly to study the brain’s role in addiction and other mental health problems. We will cover the principle behind each method, advantages and limitations of each, and provide an example of the results that can be obtained.

Beyond the Frying Pan: EEG and CT

Electroencephalography (EEG) and Computed tomography (CT) were two of the first methods used to study the brain. EEG utilizes electrodes placed on the scalp that measure electrical impulses, whereas CT creates a three-dimensional image of the brain with two-dimensional x-rays.

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More on Brainbow

Since I posted Jeff Lichtman’s Brainbows, with all those wonderful images of the fluorescent brain, I’ve gotten questions from people about two basic things: first, how do they get those colors? and second, how do they get those images?

For the colors, genetic recombination techniques are used to insert pigment-expressing genes into the genomes of developing mice. The cool part? Those extra genes come from coral and jellyfish. The red color comes from coral, while the blue and cyan come from modifying a fluorescent green pigment in jellyfish.

For the images, the fluorescent hues only appear under fluorescent light. The Lichtman group has used two techniques, both using confocal microscopy (focused image taking, rather than a normal broad view from a typical microscope). First, brain slices are taken from mice and then examined in the lab. Second, for live shots, the Lichtman group works on the “neuromuscular junctions in a very accessible neck muscle in mice,” which permits taking a series of images over several days.

In the older post I blogged on how Lichtman’s approach to his research is reminiscent of what we try to do here—a naturalist concerned with the processes, mechanisms and connections of life and an understanding of the power of observation. But here I want to point out why these techniques are powerful. First, they permit an understanding of neuronal arrangements and connections through the greater discrimination provided by the many different colors. The image below from the original Nature article shows the differences between neuronal patterns in different parts of the brain.

Second, using computers to create 3-D videos from 2-D images, this research gives us maps that permits us stereoscopic humans to actually see fields of neurons as they are structured in the brain. This too represents a major advance over older images. So enjoy the video!

Finally, for your viewing pleasure, a composite image of brainbow pictures.

How well do we know our brains?

Blogging on Peer-Reviewed ResearchMaking the rounds of neuro-related sites on the web is a recent story from Wired, Brain Scanners Can See Your Decisions Before You Make Them, by Brandon Keim. It’s an interesting short piece on an even more interesting research paper by Chun Siong Soon, Marcel Brass, Hans-Jochen Heinze and John-Dylan Haynes forthcoming in Nature Neuroscience (abstract here). But like so much in the science writing about neurosciences, the piece leaves me feeling like either I don’t get it or science writers really don’t understand the significance of basic brain research. I won’t dwell too much on my issues though with the science writer because I want to really consider the relationship between brain activity and experience, or what role phenomenology might serve in neuroanthropology (besides, I’ve been railing at science writers a bit too much of late…).

Brain areas that predict decisions. By John-Dylan Haynes. Wired.
From Keim’s article, we have this explanation of Haynes’ work:

Haynes updated a classic experiment by the late Benjamin Libet, who showed that a brain region involved in coordinating motor activity fired a fraction of a second before test subjects chose to push a button. Later studies supported Libet’s theory that subconscious activity preceded and determined conscious choice [I have a problem with that phrase, especially ‘determined’] — but none found such a vast gap between a decision and the experience of making it as Haynes’ study has….
Taken together, the patterns [in frontopolar cortex and then parietal cortex] consistently predicted whether test subjects eventually pushed a button with their left or right hand — a choice that, to them, felt like the outcome of conscious deliberation. For those accustomed to thinking of themselves as having free will, the implications are far more unsettling than learning about the physiological basis of other brain functions.

The Libet research is a classic piece (I don’t know if it makes any top 100 lists, but it’s especially important to those of us interested in motor action). The problem seems to be forcing Haynes’ data — which confirms Libet’s older research about the subconscious activity that precedes conscious awareness of ‘choice’ — through a folk theory about ‘free will’ being a necessarily conscious activity setting in motion a chain of mind events leading up to action. Folk understandings posit the existence of ‘The Decider’ in the brain, a kind of uncaused cause, the prime neural mover, which is conscious.

Bottom line, as far as I’m concerned: the research can’t be proving whether or not we have ‘free will’ because ‘free will’ is fundamentally about constraints on ‘will’ (itself a fuzzy concept when you’re looking at brain imaging). That is, the research would have to examine not what the brain does when it makes a choice, but whether that brain activity was constrained by something external to the person. After all, if we say that a person’s ‘free will’ is limited by their brain, that doesn’t really make sense now, does it? Presumably, acts of a ‘free will’ would also be determined by the brain, wouldn’t they? For the brain to ‘constrain’ our own ‘free will,’ it would have to be a thing separate from us.

What the research is showing, however, is something fascinating about the relationship of phenomenology and native categories of mind and how they might intersect with brain science research.
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Jeff Lichtman’s Brainbows

Take a genetically-engineered mouse and add color. That is what Jeffrey Lichtman, Jean Livet, and Joshua Sanes have done. Start by inserting genes that turn neurons fluorescent hues of yellow, red and cyan. Then add some more DNA that randomly expresses those three genes. Presto, rainbow brains.

As a Harvard Science piece reports, “By activating multiple fluorescent proteins in neurons, neuroscientists at Harvard University are imaging the brain and nervous system as never before, rendering their cells in a riotous spray of colors dubbed a ‘Brainbow.’ This technique… allows researchers to tag neurons with roughly 90 distinct colors, a huge leap over the mere handful of shades possible with current fluorescent labeling.”

So many colors in something as complex and elegant as a neuron produces striking images, and I have included many here. These images also permit the study of fields of neurons, from the life course of one neuron to the patterns of connections between neurons. Hence the emerging field of “Connectomics” which “attempts to physically map the tangle of neural circuits that collect, process, and archive information in the nervous system.”

I stumbled across Lichtman’s images in two publications recently. Harvard Magazine features his work, along with five other Harvard scientists, in this month’s feature article, Shedding Light on Life: Advances in Optical Microscopy Reveal Biological Processes as They Unfold. The magazine also provides an online collection of short video clips called Lights! Microscopes! Action! Across the Charles River, MIT’s Technology Review features Lichtman’s work as one of its Ten Emerging Technologies of 2008, complete with an accompanying video featuring Lichtman.

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