Brainbrawl round-up

Columbia University hosted a debate between Tony Movshon and Sebastian Seung last Monday, “Does the brain’s wiring make us who we are?” This became known informally as “brainbrawl.” I watched it livestreamed through the Radiolab site, and someone had the wherewithal to grab the video below (which Radiolab said they weren’t planning on archiving). Radiolab did archive the live chat here.



Where’s the fight?

As I predicted, it was a much more sedate affair than the “brainbrawl” moniker suggested. Seung set the tone in his first comments by pulling back from the big claims that he has made previously. Instead of discussing the nature of human identity (his TED talk) or immortality (his book), he was much more circumspect in outlining what a connectome could do for us. Near the end, he said, “All I want to do is map some connections!”

I liked this, actually. It is a far more sensible view of the promise of connectomes than we’ve sometimes seen. But yes, it would have been more fun if Seung had swung for the fences anf salked about uploading consciousness. At the end, co-moderator Robert Krulwich was apologizing for the lack of blood on the floor and the modesty of the speakers.

The fight (to the extent that there is a fight), then, is not about whether connectome research is feasible or useful, but about grand challenges and resources. Movshon nailed it when he said people are looking for “gigascience” projects, and that neuroscience has been a “cottage industry.” While nobody said it directly, “gigascience” is often about making a sales pitch. People want to be at the forefront of establishing big projects, because the prospect of money is there. Someone made a comment about keeping score, and Movshon said, “The NIH is.” Krulwich asked Movshon, “What’s your recruiting pitch? What do you tell the young mavericks to bring them into the field?” (Krulwich occasionally seems to confuse science with the Wild West; also here.)

It seems to me like Seung talks about connectomes as a way to pitch his research, which involves developing techniques to do high-throughput neuroanatomy (e.g., Jain et al. 2010; he talks about this more in this interview with Jennifer Oulette). Faster, more automated electron microscopy would be a godsend. But I doubt Columbia UNiversity would have hosted a debate on, “Should we develop better EM?” One commenter on Twitter said:

I haven't heard alternatives to connectome that generate comparable ideas/excitement

I’m not sure we need it. It’s not as though neuroscience is suffering for people; remember, we hold the biggest scientific meeting in the world. personally am unconvinced that we need grand challenges in science. The history of science shows that the way you answer the big questions is by answering the small questions.

The invertebrate in the vertebrate brain

Invertebrates came up in the discussion a couple of times. Good circuit descriptions of the mammalian retina are actually fairly far along, and may be the first part of the brain for which we have a connectome. Seung commented, however, that the retina was like an invertebrate brain contained within a vertebrate brain. I think he was referring to several of the retinal cells being non-spiking, which is also true of the worm Caenorhabditis elegans.

On Twitter, Noah Gray said he didn’t think C. elegans informed the connectome debate at all, because it has non-spiking neurons. I disagree, but at the very least, it does point out the importance of the intrinsic properties of neurons. Movshon suggested that the reason that C. elegans had non-spiking neurons was that it was small. This is too simple an explanation. In crustaceans, you can find both spiking and non-spiking proprioceptive sensory neurons (e.g., Paul and Wilson, 1994), and there seems to be no readily apparent functional reason to favour one or the other.

As I’ve mentioned before, we have a connectome of C. elegans, and there was discussion about how useful it actually it. In his book, Seung admitted that the connectome hadn’t solved all the neurobiological research problems for that animal, but that it might be a special case. Seung tried to argue that C. elegans posed technical problems in recording from the neurons, but Carl Zimmer pointed out that if his hypothesis was true, that wouldn’t matter. I do think the moderators, and possibly Movshon, were too dismissive of what we have learned from the connectome of C. elegans. Seung is correct that the connectome is very important to guiding research in the nervous system of the animal.

What occurred to me, though, was that there might be another invertebrate example that shows the usefulness of determining neuronal circuits: the eye of the horseshoe crab.

Haldan K. Hartline won the Nobel prize for his work on horseshoe crab vision. Hartline was able to map connections between the photoreceptors in the crab’s eye. He had the advantages that the photoreceptors were spiking neurons (unlike in mammals), and that there was only one type of photoreceptor. That is, each was an interchangeable widget, and the properties of the neuron were largely determined by connections with other neurons. By figuring out the simple circuit in the eye, he showed how lateral inhibition was able to enhance contrast of edges. This is important because the horseshoe crab eye has very low resolution.

Many years later, Robert Barlow and colleagues used a connectome-like model to build a biologically realistic model of the horseshoe crab retina and the signal it sends to the brain (Passaglia et al. 1997; Barlow et al 2001). When it was published, it was the largest biologically realistic model that had been built. They showed that some previously puzzling features of the synapses, like neurons inhibiting themselves, did things like filter out flicker in the environment.

If the mammalian retina is an invertebrate nervous system trapped in a vertebrate brain, the horseshoe crab retina may be a vertebrate nervous system in an invertebrate brain.

Other tidbits

I liked Movshon’s comment that the brain is not a multi-purpose computer, but a specific purpose computer. That is, brains are the products of natural selection and need to do specific things very well. This contrasted with his earlier argument against studying connectomes by using a well-worm software analogy, used my many cognitive pyschologists: "Studying the hardware doesn’t tell you anything about the software.” True for your desktop computer, but the brain is not an electronic computer, as Seung noted.

The audience asked some very smart questions. I wished they’d had a chance to ask more.

References

Barlow R, Hitt J, Dodge F. 2001. Limulus vision in the marine environment. The Biological Bulletin 200(2): 169-176. DOI: 10.2307/1543311

Jain V, Seung HS, Turaga S. 2010. Machines that learn to segment images: a crucial technology for connectomics. Current Opinion in Neurobiology 20(5): 653-666. DOI: 10.1016/j.conb.2010.07.004

Passaglia C, Dodge F, Herzog E, Jackson S, Barlow R. 1997. Deciphering a neural code for vision Proceedings of the National Academy of Sciences of the United States of America 94(23): 12649-12654. PMID: 9356504

Paul DH, Wilson LJ. 1994. Replacement of an inherited stretch receptor by a newly evolved stretch receptor in hippid sand crabs. The Journal of Comparative Neurology 350(1): 150-160. DOI: 10.1002/cne.903500111

External links

Rockstars of neuroscience (and their fans) turn out to debate the future of brain studies
A heavyweight brain debate
The value of the connectome: Seung and Movshon Debate
Brainpickings review of Connectome
Storify of the event by Stanford students
Google Plus discussion from Pascal Wallisch.

Another reminder of what people think of professors

A student organization asked in a medical professional to come give a talk this week.

During this talk, this physician told the students that some their professors had “a chip on their shoulder” because couldn’t get into medical school, and took it out on students by refusing to give them As.

That ticked me off a little.

I have chips aplenty on my shoulder. But none are because I wanted to get into med school and couldn’t. I don’t know of any professor who was a failed med student.

Coming in May, 2012

Here’s a teaser trailer for a highly anticipated new project coming out in May... The Avengers? Heck no. May is the start of the next round of #SciFund!

Science careers: fair play or field of bullets?

Yesterday, Elizabeth Sandquist posed an hypothesis:

You can't just be good to succeed in #science, you have to be exceptional. Any thoughts?

NeuroPolarBear replied with a post, and Drugmonkey pulled out an older post.

But my post will be the best, for I shall cite peer-reviewed data in the primary literature.

As it happened, Petersen and colleague published a paper yesterday looking at career success in physics. Appropriately enough, even though it’s a career paper, it feels very much like a physics paper: lots of equations and models and phrase like “leptokurtic but remarkably symmetric.” Hoooookay...

The authors tracked 300 physicists through about 20 years of their careers. They fell into three groups: phsyicists who were eminent (h -index of 61); productive and highly cited (h-index of 44), and early career assistant professors (h-index of 15). In that data from real scientists, Petersen and colleagues see that there are time when physicists are “shocked.” The shocks can be positive (“Wow, I just made this totally great discovery by accident!”) or negative (“Uh oh, they found that paper where I manipulated data.”)

They also look at career productivity, and the ability of researchers to build collaborations.That’s the “ground truth” that Petersen and colleagues use to create models of research career trajectories. This lets them play with some of the parameters.

The models indicate that as competition increases, many people can be taken out of the career pathway by... blind, stinking, clueless, doo-da luck.

Those that survive the field of bullets reach a point where they can start generating collaborative networks, and that builds even more success.

But the competition turns out to be very important in this model; and that relates to tenure. Many people want to see tenure replaced with a series of recurring short-term contracts. The authors imply that the short-term model could be harmful for the development of science. A failure in one short-term contract could derail a productive researcher, since early career shocks can ripple throughout a scientist’s career.

I think Petersen and colleagues would say that you do not have to be exceptional to make it in science. More important is the ability to tough out the early weeding out period, which doesn’t necessarily have a lot to do with your talent.

Reference

Petersen A, Riccaboni M, Stanley H, Pammolli F. 2012. Persistence and uncertainty in the academic career Proceedings of the National Academy of Sciences 109(14): 5213-5218. DOI: 10.1073/pnas.1121429109

Tuesday Crustie: Prefab

This is going to be the crustacean story in the news all this week for sure...

It’s a hermit crab. His name is Harry. His is wearing a Lego shell, which is not surprising, given that he lives in an aquarium in a UK amusement park - Legoland.

This is from a Guardian story here. This picture doesn’t do justice to the accompanying video (can’t embed it, so if you want to see it, you’ll have to hit the Guardian’s website).

The article implies that the crab chose this shell over more regular snail shells. The story doesn’t make clear that the shell is not entirely Lego. In this preview image on the video (which is often partly covered by the “Play” or “Replay” icon), you can clearly see the molluscan shell that the Lego shell is built onto:

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Update, 4 December 2025: The Press Association contacted me to inform me that the pictures in the post were unlicensed. So I have removed the images. The original article about Harry the hermit crab and his Lego shell is still available in The Guardian.

Brainbrawl! The Connectome review

Recently, I wrote a post discussing connectomes. (Recap: Connectomes are descriptions of every synaptic connection between neurons in a brain.) In it, I referred to a paper by Cornelia Bargmann and argued that the amount of enlightenment we will gain about ourselves through connectomes is being oversold. I used several quotes from Sebastian Seung as examples, and mentioned his book on the subject.

Sebastian Seung noted that I had not read his book. Fair enough. I was not trying to single out Seung, but I can see that my post uses his examples enough that it seems like I am reviewing the book without reading the book.

I bought the book and read it.

The timing has turned out to be good, for today, Carl Zimmer and Robert Krulwich are moderating a debate between Seung and Anthony Movshon at Columbia University. The formal title of this debate is, “Does the brain’s wiring make us who we are?”

The Twitter hashtag? #brainbrawl. Much more fun, although I worry it promises more sparks than one will probably get from an academic debate about neuroscience. For example, The description of the #brainbrawl debate ends with the question, “Are brain maps the future of neuroscience or an empty promise?” I doubt anyone will argue that describing connectomes will yield nothing. As I said, even though I think the enterprise will fail, on some level, it will fail in an interesting and productive way.

Additionally, Seung was recently profiled in Discovery magazine by Zimmer and Wired. The other #brainbrawl moderator, Robert Krulwich, examines the issues behind “Jennifer Aniston neurons” here, and examines mapping, asking “To map or not to map the brain?”

Early in Connectome, Seung says:

This book proposes a simple theory: Minds differ because connectomes differ.

I read through, making notes, and was caught off guard in the last chapter. After spending all this time making arguments for his connectome theory, I was surprised that in the last chapter, Seung surrenders the war.

Yet Seung remains optimistic that he can win one battle.

In Chapter 4, Seung argues that the function of a neuron is determined primarily by its connections with other neurons. Take a neuron from one region of the brain, stick in into another part of the brain, hook up the input and output synapses the right way, and away you go.

To put it another way, Seung initially treats neurons as interchangeable widgets.

At this point, I was getting ready to start a big long list of reasons why neurons are not interchangeable. There are not only neurons that generate action potentials, there are neurons with graded potentials, pacemaker potentials, and plateau potentials. There are the passive electrical properties of the dendritic tree. These are just a couple of examples of the long list of intrinsic properties of neurons that make them distinguishable by far more than their connections to other neurons.

These are all in addition to changes of neuronal physiology introduced by neuromodulation.

Seung addresses the intrinsic properties of neurons in the book’s last chapter:

In principle, every neuron is unique in its behavior, owing to the unique configuration of its ion channels. This is a far cry from the weighted voting model, according to which all neurons are essentially the same. But it sounds like bad news for brain simulation. If neurons were infinitely diverse, how could we ever succeed at modeling them? Measuring the properties of one neuron would tell you nothing about another.

There is one hope for escaping the morass of infinite variation: neuron types.

The concept of neuron “types” is initially introduced in Chapter 10. Seung initially wants to categorize the neurons by their connections.

If two neurons are connected to similar or analogous partners, they should be grouped in the same type.

Seung then makes an extrapolation that is plausible, but I would say not yet proven: neurons with similar anatomical connections will have similar physiology and other intrinsic properties.

(N)eurons of the same type generally exhibit the same electrical behaviors. This is presumably because their ion channels are distributed in the same way. If this is the case, then neural diversity is actually finite.

By this point in the book, Seung has already introduced the only complete connectome of any animal, that of the 302 cell nervous system of the worm, Caenorhabditis elegans. I expected that this would be used as the flagship case of how connectomes can help us understand behaviour.

Instead, Seung declares defeat.

He estimates that of the 302 neurons in C. elegans, there are about 100 different types of neurons. And that proportion of distinct neuronal types, he says, is too high for a purely connection-based model to explain the worm’s behavior.

As you read this section (emphasized sections are mine), recall that he's been repeated the mantra, “You are your connectome,” for the previous 14 chapters. Now, in the very last chapter, an important missing piece gets added.

Thus the earlier claim should be revised to say, “You are your connectome plus models of neuron types.” (Let’s assume that a connectome is defined to specify the type of each neuron.) But the models of neuron types are likely to contain much less information than the connectome, as most scientists agree that there are far fewer neuron types than neurons. In this sense, “You are your connectome” would remain a very good approximation.

So “You are your connectome” would be a terrible approximation for a worm, even though it might be almost perfect for us.

If Seung is not convinced that the connectome theory yields meaningful information for C. elegans, I am skeptical that the ratio of neuronal types to the total number of neurons in a human brain^* is going to be more favourable to connectomes explaining the mind.

At the very least, we have to acknowledge that there is a continuum.

One one end, we have circuits in which activity is dominated by few types of neurons, in which understanding the synaptic connections explains a large proportion of the function. Escape circuits are excellent examples, such as those in crayfish and fishes.

On the other end, we have circuits that are composed of many personalities, and where the intrinsic physiological state of the neuron matters a great deal to the function. Seung suggests C. elegans falls into this category, and I’ll suggest the crustacean stomatogastric nervous system as another.

It is not clear to me where regions of human brains may fall on this continuum. When I visited the Neuroscience department at the University of San Antonio recently, and was discussing my previous post, several people indicated to me that those interested in connectomes placed special emphasis on the cerebral cortex, apparently because those neurons are a little closer to the “interchangeable widget” end of the scale than other brain regions.

Losing the war - the ability of connectome theory to explain large parts of behaviour in many species - may not matter for Seung, however. For Seung, like many neuroscientists, there is only one battle worth fighting, the one for human minds. Near the end of the book, he writes:

(T)here is only one truly serious problem in science and technology, and that is immortality.

The last sections of the book deal with topics like transhumanism, immortality, and putting consciousness into computers. These are a very distinct group of pre-occupations, all revolving around human consciousness.

As a neurobiologist, I want a theory that can explain how nervous systems generate all the behaviours of all the diversity in the animal kingdom. A theory that only explains the human mind is a small and paltry thing.

Connectome theory reminds me of Anne Elk's theory:



In one sense, the theory is trivially true. But in another sense, the theory omits so much that it doesn't end up telling us anything we wanted to know.

Reference

Seung S. 2012. Connectome: How the Brain's Wiring Makes Us Who We Are. New York: Houghton Mifflin Harcourt. 384 pgs. ISBN: 978-0-547-50818-4

^* Seung uses an estimate that the human brain contains 100 billion neurons. More recent estimates put the count closer to 85 billion neurons, which he could not have had given the lead time of publishing a book.

Comments for second half of March, 2012

Drugmonkey looks at the chase for perfection in a scientific career.

Matt Shipman weighs in on the question of whether a science journalist should be able to read and understand a scientific paper.

How long does it take you to write a scientific paper? Code for Life investigates.

Does the Deep Sea Challenge mean science is a rich man’s game?

Scicurious hates networking. The comment thread is pretty darn helpful, too. Some threads were picked up in Dr. Becca’s blog looking at conference size.

Where’s the science love, Twitter? Chris Dieni feels unloved and unanswered by the Twitterverse.

Dr. Doyenne looks at the good science on YouTube.

Whaddya wanna talk about?

After reading Scicurious’s rant about the difficulties of networking, particularly at conferences, I got to thinking. Several people in the comments talked about the intimidation of trying to talk to more senior researchers. Let’s flip it around, look at it from the point of view of the senior researcher and ask what they want to talk about.

What are my favourite conversations to have at scientific conferences?

Conversations that help someone.

I like helping other people at conferences. At the risk of sounding kind of selfish and needy, I want help, too. Help with current projects. Help with ideas for future projects. Help getting publications. Help getting funded. Help figuring out why reviewers hate the manuscript when people at conferences give the project positive feedback.

Maybe a way to start thinking about networking is to ask, “How can I help?” and “What do I need help with?” How can you create opportunities for another person at a conference?

Conversations that simply acknowledge what I do are also high on my list of talks I like to have. A lot of the time, publishing scientific research feels like shouting into a vacuum. My friends and colleagues in my own department don’t read my papers (which is fair, because I rarely read theirs). You think your blog doesn’t get enough comments? Try waiting years for citations to start coming in. When someone that I do not personally know tells me, “I read your paper in this journal,” I just want to take that moment and polish it until it shines like a shiny stone. It doesn’t even matter if they liked the paper; just that they’ve read it is more than enough.

Along those lines, people who says they like my blog is at higher than usual risk of getting hugged on the spot, even if we've never met before and I have no idea of who they are.

But don’t confuse acknowledgment, or even compliments, with flattery. Acknowledgement is genuine; flattery is manipulative. Compliments are sincere; flattery is not. I hate it when someone tries flattery, because it’s usually obvious and clueless. Don’t tell me that you admire my “world famous” work. I know my place in science better than that, and I don’t need my ego stroked.

We’re told to network for the same sort of reasons that we tell undergraduates that they have to learn calculus: “Because it’s worth points and you’ll need it later, trust me.” You need to get something out of it. Let’s abandon the directive that you must network because, well, “You just gotta!”

Networks grow out of conversations. If you take care of the conversations, the network will take care of itself.

What conversations do you want to have at conferences? That’s not a rhetorical question. I genuinely want to know.

Science portfolios

I’ve had several reminders this week about the importance of having students do stuff. Not just answer questions.

• This video has a lot of interesting stuff about embodied cognition. We think better when we move. (Hat tip to Julie Dirksen.)
• This video a reminder about how chasing points can kills motivation.
• I have a student trying visual notetaking who’s showing improvement (hat tip to Sunni Brown; for a great introduction of visual notetaking, see here).

These reminded me of an idea that’s been rattling around in my head for a while.

Rather than having students turn in a series of prescribed assignments, I want to have undergraduate students develop a portfolio of work.

Portfolios are common in the arts. A scientific CV is sort of a portfolio, with publications being the representative works. Publications are just typically looked up rather than looked at. But ultimately, the goal of both is to have a collection of finished, tangible products to show off.

I like the idea of students making something that they can show off a lot. Because ultimately, their potential employers or supervisors they’ll work with after they graduate are going to want someone who can make stuff and deliver it.

The problem is that I’m not quite sure what a portfolio for an undergraduate science student might look like.

I’ve come close to the portfolio idea in my writing classes. I’ve often had students create a blog, with the idea that it might be something they can point to at the end of the semester as an accomplishment. Of course, there’s other kinds of other content that you could create for the Internet; podcasts and videos are obvious choices.

But there my ideas run dry.

What else could an undergraduate create in the course of a semester? Something that at the end of the semester, they could point to and say – maybe even with a little pride – “I made that.”

Picture by Jason Schlachet on Flickr; used under a Creative Commons license.

PACE Bioethics 2012

One of the things that made last week absolutely frantic was that the annual PACE ethics conference, It ran during the last half of the week. Any time I didn't have a meeting, I tried to be in the conference. Here's a quick rundown of some of the highlights that I saw.

On Wednesday morning, I introduced one of the keynote speakers, Robin Fuchs-Young. Robin has visited our campus before many times, including once as an REU speaker. She spoke about the evolution of ethical regulations in research, mostly in the United States. One of the recurring themes in her talk was how recent many regulations and policies were. After the talk, she told me that preparing for this presentation that helped her realize that, "We're not doing a very good job of introducing our students to these issues."

This was immediately followed by a panel I was on, titled, "Would you trust a robot surgeon?" This panel was meant to be about fears of new medical technology generally, although it got a bit more focused on the robotic surgery than I initially expected. There was some interesting discussion of the psychology of who adopts new technologies in any endeavor, not just medicine.

I was on the panel because I was saw some parallels between whether people trust medical technology and science denialism. Indeed, one person at the audience started talking about how the use of any new technology should be made by patients weighing the pros and cons. I pointed out that this was a very academic way of looking at things, and people often don't make decisions based purely on information. I noted that arguably the most successful medical technology in history, the only one that has permanently rid the planet of two diseases, is widely distrusted, even by reasonably highly educated people.

In the afternoon, I watched a panel titled, "Ethical Complications of Perpetual Competition." What blew me away was that what seemed to me to be the most obvious potential complication to competing all the way from K-12 to residency - the temptation to cheat - was never mentioned. One of the things that did come out was that there are some big changes planned for medical education. There's some discussion about creating something like a "Medical humanities" major, so that the medical schools do not just have biology and chemistry majors.

I spent late afternoon and early evening chatting with fellow blogger Janet Stemwedel, a.k.a. Doc Freeride. And the rumors are all true: she's just an amazingly cool person.

It's a fascinating experience to meet someone face to face who you're followed online for years. The online persona captures a lot, but not everything. Her blog doesn't always convey her quirky sense of humour, which is abundantly evident face to face. But anyone who says you can't build real dialogue through online interactions is wrong.

We sat and listened to the evening keynote, by local physician Carlos Cardenas. Cardenas's argument was his criterion for judging health policy: anything that interferes in any way with the relationship with the doctor and a patient is bad. While I appreciated that he was trying to emphasize trust and human connections, his point of view undervalued that any physician is a member of a professional community.

On Thursday, I couldn't miss Janet Stemwedel's keynote. Janet gave a great talk about how many biomedical students think that they can avoid worrying about ethical issues by working with materials in a dish. But using Rebecca Skloot's The Immortal Life of Henrietta Lacks as a guide, she showed that you don't get a pass on ethical dilemmas just because you're working with tissues and cell lines.

A couple of things stood out to me. One was that the ethics got sticky because the list of relevant stakeholders kept expanding, in an unpredictable way. Nobody knew much about DNA when the HeLa cell line was started; it was only much later that genetic technologies brought Henrietta's family back as stakeholders. The other point that Janet made, echoing Robin's from the day before, was how much ethical policies around research are crisis driven. It's fairly common for policies to be created after problems have occurred, rather than being written in anticipation of problems.

The last panel I saw, in the afternoon, concerned violence, particularly against women and vulnerable groups, as a health care problem. More so than the other panels I had watched, this one focused more on local issues and problems. For instance, the local availability of nurses trained to do examinations for sexual assault, and that there is no medical examiner's office in the region.

One undercurrent that I sensed several times though the conference - and maybe I'm reading between the lines too much - was suspicion of government. After the technology panel I sat on, a local nurse got up and was talking local health care, rather enthusiastically. At some point, she talked about what made "us" great was "our freedoms." I think she may have even snuck in a mention of either the founding fathers, the American constitution, or both.

During the competition panel, one phsyician talked about government being in competition wit physicians. In his evening keynote, Cardenas said:

(N)ot one insurance plan ever cured a patient, much less held their hand, and no set of laws written by policy makers in Washington or Austin ever truly saved a life(.)

This was a rather surprising claim to me. I can think of plenty of laws that have saved huge numbers of lives. Seat belt legislation. Safety regulations. Restaurant health inspections.

I suspect I raised my eyebrows, too, when someone in the audience at Cardenas's keynote complained that physicians weren't listened to in policy discussions. I'm almost certain my eyebrows crawled up my forehead when this individual said that if they were allowed to, physicians could solve all the problems in about five minutes.

I'm hoping that was meant to be funny. But I'm not sure it was.

I understand frustration with legislators. I've often said I've been surprised by how much Texas lawmakers want to dabble with universities, for instance. But I don't think I would ever say that we professors could solve it all during a coffee break if people would just listen to us.

I kept sort of waiting for someone to jump up and say, "Ron Paul 2012!"

Janet Stemwedel has blogged about her thoughts here. The university's summary is here.

Prepare yourself

If you are a researcher, you have only until the end of this week to sign up for round 2 of the #SciFund Challenge! Go here to sign up!

Last time, SciFund raised $75,510 dollars, and ten out of 49 projects met or exceeded their funding goals. And it was pretty darn fun.

Round two of SciFund will run through May!

Tuesday Crustie: Smorgasbord

Decisions, decisions... what kind of crustacean to feature on the Tuesday Crustie feature today?

I choose not to decide!

I don’t recognize the exact species, but I recognize a few cousins to species I’ve studied.

Photo by hyperion327 on Flickr; used under a Creative Commons license.

More accusations of professor laziness

Aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaand it’s yet another piece claiming that professors are lazy, this time from the Washington Post.

Here's the crux of the argument: Professors at research universities work hard, but we all “know” that only a tiny fraction of universities actually do research, and those people don’t work hard enough (emphasis added).

The faculties of research universities are at the center of America’s progress in intellectual, technological and scientific pursuits, and there should be no quarrel with their financial rewards or schedules. In fact, they often work hours well beyond those of average non-academic professionals.

Unfortunately, the salaries and the workloads applied to the highest echelons of faculty have been grafted onto colleges whose primary mission is teaching, not research. These include many state colleges, virtually all community colleges and hundreds of private institutions.

Speaking as someone at a state university, we have research expectations. And they’re increasing. Indeed, it is arguably more difficult and time consuming to conduct research at an institution with a history of being primarily teaching, because there is less infrastructure and support.

To say that only a tiny number of universities should conduct research is a huge waste of talent and opportunity. Indeed, one of the things that we should be teaching our students is how to conduct research, which requires working individually with students. One of the side effects of these kinds of proposals is that they enhance the Matthew effect at universities: big research universities protect their turf and accumulate more resources, prestige and opportunity, while other universities – and the communities they serve – get less and less done.

And, not surprisingly, the amount of teaching expected does scale with research expectations. Teachers at an emerging research institution like my own teach less than at a community college, but more than a research intensive institution.

There’s a more subtle bias, here, too. It’s the notion that researchers are worth more. Teaching isn’t being valued. Yes, this is couched in terms that researchers put in more hours. However, this editorial provides no evidence that researchers at highly intensive research institutions work more hours than instructors at community colleges and state universities.

The article continues a fine tradition of underestimating the time it takes to prepare and grade students.

Even in the unlikely event that they devote an equal amount of time to grading and class preparation...

Unlikely? In many classes, particularly more advanced classes, the time spent preparing and grading can easily exceed the time in front of a class several times over.

The article also overestimates some of the advantages of being a professor. According to Levy’s piece, professors not only get tenure and “light” teaching loads but “long vacations and sabbaticals.”

By long vacations, I am guessing the author means “summer.” Do you know most academics get nine month appointments? We don’t get paid for summer, unless we teach in summer 9which at our institution is a separate budget and not guaranteed).

I have never had a sabbatical. In my entire department of about twenty faculty, exactly one professor in our department has had a sabbatical. To get that, he sought and received an external grant to pay for it. (And the program is limited to American citizens, so I am not eligible to try for it. But I’m not bitter.)

The other issue with looking at wages of people at the very end of their careers is that it overlooks that training to be a professor takes a long time. In my case, I was in training for over 15 years. There needs to be some acknowledgement of compensation over the course of a career, not just at the very end of a career, with what “top” (most senior) professors earn.

It’s also noteworthy that part of this editorial’s “advantage” of increasing workload is that we would need fewer professors, just in a time when there is a job shortage.

Additional: More discussion from Kristina Killgrove on G+.

More additional, 26 March 2012: Janet Stemwedel, College Guide (with data showing professors are not responsible for driving up tuition costs), and Gin and Tacos.

Hat tip to Neuropolarbear for harshing my mellow on a Sunday morning. Thanks to Scicurious and Katiesci and Cedar Reiner and Kari and other folks for Twitter discussions.

The Zen of Presentations, Part 53: Doing it vs. talking about it

When you are in the thick of a project, the time you spend getting stuff done might look like this.

Because of how much time you have spent learning that technique, getting some initial preliminary results, then having it mysteriously fail for no reason, troubleshooting, learning that your boss calls part of the technique “black voodoo magic”, offering sacrifices to the lab gods, it is understandable that when you are given the chance to talk about that research... you spend the same amount of time describing those techniques.

I think this is particularly a trap for people who are just coming into a project. When I learned a new technique, I was so excited about this technique giving me my first data that I focused too much on the technique, and not enough on the data.

It’s worth noting that in research articles, the methods section is often set in small text or placed last in the article, after the conclusions. Both of these are good indications that descriptions of techniques and methodologies are fine print. Relatively few people are going to be tremendously excited by how you optimised your buffers, or found a great way to manipulate data in Excel.

The breakdown might look more like this.

Many presentations jump into the details way too fast. A lot of good technical presentations are characterized by long introductions. Having an introduction take up half your talk is not out of the question. The data that answers a question and what you conclude about it should make up most of the rest.

The time you spend talking about stuff you did in your project need not – indeed, should not – bear much relationship to the amount of time you spent on that task.

Related posts

Poster Venn (Better Posters blog)

The myth of fingerprints

Could you have made a mistake?

If you are a fingerprint examiner in court giving testimony, the answer was once, “No,” according to Mnookin (2001).

(T)he primary professional organization for fingerprint examiners, the International Association for Identification, passed a resolution in 1979 making it professional misconduct for any fingerprint examiner to provide courtroom testimony that labeled a match “possible, probable or likely” rather than “certain.”

(I’ve been unable to find is this is still true.)

A new paper by Ulery and colleagues is a follow-up to a paper they published last year on fingerprint analysis. The previous paper found 85% of fingerprint examiners made mistakes where two fingerprints were judged to be from different people, when in fact they were from the same person (false negative). There was much more analysis, but you get the idea.

The researchers wanted to see how consistent the decisions were after time had passed. For this paper, they used some of the same fingerprint examiners that had been tested before (72 of 169 from he previous paper). It had been seven months since the fingerprint examiners had seen these prints. They were all prints that they’d seen for the previous research, but Ulery and colleagues didn’t tell them that.

Because the experimenters wanted to see if examiners who had made a mistake before would make the same mistakes again, the choice of what pairs of fingerprints to make was somewhat complicated. But all examiners saw nine pairs fingerprints that were not matched (from different people) and sixteen pairs that were matched (same people). And it’s also important to note that the fingerprints chosen were chosen in part because they were difficult.

In the original test, the fingerprint examiners only rarely said two fingerprints were from the same person when they weren’t (false positives). On the retest, there were no cases of false positives, either repeated mistakes from the previous test or entirely new mistakes.

The reverse mistake, the false negatives, were more common. Of the false negative errors made in the previous paper, about 30% were made again in the new study. And the examiners made new mistakes that hadn’t been made before.

There is some good news here, however. One piece of good news in this paper is that in some cases the examiners’ ratings of the difficulty were correlated with probability they would make the same decisions as before. But he examiner’s ratings of difficulty, however, only weakly predicted the errors that they made.

Another important finding is evidence that the best way to reduce errors is to have fingerprints examined by multiple people, rather than multiple examinations by the same person. The authors write:

Much of the observed lack of reproducibility is associated with prints on which individual examiners were not consistent, rather than persistent differences among examiners.

Nevertheless, even with two examiners checking fingerprints, Ulery and colleagues estimate that 19% of false negatives would not be picked out by having another examiner check the prints.

These papers all concern decisions made by experts, which is obviously the logical place to start from a policy and pragmatic point of view. As an exercise in seeing how expertise develops, tt would be interesting to see if beginners showed the same types of patterns in decision making.

References

Mookin JL. 2001. Fingerprint evidence in an age of DNA profiling. Brooklyn Law Review 67: 13.

Saks M. (2005). The coming paradigm shift in forensic identification science Science, 309 (5736), 892-895 DOI: 10.1126/science.1111565

Ulery B, Hicklin R, Buscaglia J, & Roberts M (2012). Repeatability and Reproducibility of Decisions by Latent Fingerprint Examiners PLoS ONE, 7 (3) DOI: 10.1371/journal.pone.0032800

Photo by Vince Alongi on Flickr; used under a Creative Commons license.

Tuesday Crustie: Celebration!

Various species. Their identity uncertain, but they seem to represent caridian shrimps, and anomuran crabs and squat lobsters (too few large legs on the ones in the upper right and lower left to be astacideans or brachyurans).

Photo by Wyrmworld on Flickr; used under a Creative Commons license.

The nano scale, fingernails, and using yourself as a research subject

A nanometer is one billionth of a meter. It’s hard to visualize something that small. To try to put it in understandable terms, Robyn Williams said this on The Science Show (I think).

By the time you finish this sentence, your fingernails will have grown one nanometer.

And for some reason, that little claim stuck with me. I kept wondering, “Is that accurate?”

Last fall, I asked students in my Biological Writing class to estimate how much time it would take for fingernails to grow one nanometer. We had talked about Fermi problems in class, using some examples in the book Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin (Amazon). Out of 13 estimates, eleven ranged from 0.09 to 1.6 seconds, and I had two outliers of 60 and 600 seconds.

But estimates just weren’t good enough. I wanted real data. When the new year came, the next time I trimmed my fingernails, I opened up a spreadsheet and wrote down the date. When I needed to cut them again a few weeks later, I got out calipers that could measure to 0.01 mm. I measured each fingernail at three points to get an average rate of growth and to even out irregularities from my cutting the nails.

I was going to measure the rate of growth (nanometers per second) five times. I managed to fracture a couple of my nails at one point, making correct measures of length tricky for them, so I went another time. I ended up with five or six measures of growth rate for ten fingers.

The results of my somewhat obsessive self-study:

An average fingernail growth rate of 0.92 nM / sec. My Biological Writing students had come up with quite decent estimates – certainly better than you’d get by just guessing! The mode estimate from the class was that it would take about one second for a fingernail to grow one nanometer.

I was a bit surprised to see that growth isn’t as even as I might have expected. It fit my subjective impressions that the ring fingernails looked like they needed trimming first, though I wouldn't have expected the middle fingernail was growing just as fast.

Getting back to the original claim, we need not only the rate of growth, but the time of the sentence. It took me about 3.77 second to say, “By the time you finish this sentence, your fingernails will have grown one nanometer” (n = 10, timed with stopwatch).

This means that the original claim is quite conservative! By the time you finish saying that sentence out loud, your fingernails will probably have grown something like three and a half nanometers (3.47 nM, if you wanted to be precise), not just one.

The anti-calm poster

This one is Becca’s fault...

More appropriate for those in grad school, tenure track... academia generally.

Comments for first half of March, 2012

Scicurious offers advice on writing a dissertation.

Jason Snyder looks at differences in citation report databases.

What’s the craziest thing you’ve done for science?

io9 reports on science crowdfunding.

The Cellular Scale looks at action potentials in an iconic meat eating... plant.

Calling South Texans!

Have you seen the items in this gentleman’s hands?

Whale shark researcher Dr. Al Dove reports that these GOS tags have been found near Brownsville, Texas. He would like them back!

If you are a local here in South Texas, please help spread the word. If you get them, send him a tweet: he’s @para_sight on Twitter.

Additional, 16 March 2012: This was featured on one local television station’s evening news broadcast. I’m glad the story spread, though we are still looking for these!

The Zen of Presentations, Part 52: Big finish

Two people go in for a rather invasive and somewhat painful surgical procedure. The nature of the procedure means that the can’t be anesthetized. To keep track of their pain, the physicians ask the patients to rate the level of pain they’re experiencing at regular intervals, from one to ten. Imagine this is charted below.

When the red line hits “0”, it’s because the procedure was done.

Some months later, on a follow-up, the patients are asked to describe their overall experience.

You would expect the patient whose responses that are plotted in blue in the chart above would report the experience being much worse. If you add all the numbers, this person’s average pain was higher, and they were in pain for much longer.

The patient whose responses are in red usually reports the experience being much worse than the patient whose responses are in blue, even though this person’s procedure was shorter, and they were in less pain overall. Why?

Endings matter.

The entire experience is profoundly influenced by that last memory. The patient in red ends in almost excruciating pain; the patient in blue ends with mild discomfort. And that last experience tends to be one that sticks.

This might explain why twist endings in movies and television and other stories are so divisive. They can be spectacularly successful or agonizingly bad. Sometimes a great ending saves an movie or episode and turns the run-of-the-mill into something quite amazing (e.g., The Sixth Sense). How many times have you been going alone, carried along with a story... and the ending ruins it, and you leave with a sour taste in your mouth? (E.g., Jacob’s Ladder.)

This talk - the most popular Ignite! talk to date - could be significantly improved:



This talk is popular because it is so useful. But the ending... a recap? What do you need a recap in a five minute talk for? Peoples’ memories aren’t that bad.

Nancy Duarte nailed what an ending should be in her book Resonate: a vision for a better tomorrow. She calls it, “the new bliss.” The new bliss sets out what could be, if the audience takes the story you have told them and acts on it.

Here’s a great example of an ending that lays out a new bliss. It’s Hans Rosling talking about the magic of washing machines:



A world with washing machines is not just a world with clean laundry. A world with washing machines is a world where machines have freed up time for parents to read books to their children.

In a scientific talk, the new bliss can be something as simple as a more complete understanding of some fine theoretic point that people in your field will appreciate. It could be ruling out an hypothesis. Or it could be a shifted paradigm. Or maybe there are big potential practical spin-offs that could come out of the work.

Put a lot of work into your endings.

Note: I heard the patient story on an online video somewhere; I thought it was on the TED website, but can’t find it gain. If anyone recognizes this and can point me to it, I would be most grateful!

Tuesday Crustie: Headline news

Because really, kids should be getting IACUC training much earlier.

Okay, this is a cheat: there is no actual crustacean in this picture. But I love this headline too much. Better without context.

Photo by Gerry Balding on Flickr; used under a Creative Commons license.

Neuroscientists Talk Shop

When I was at the University of Texas San Antonio last week, I recorded an interview with them for their Neuroscientists Talk Shop podcast. Mine is now up. It’s mostly about nociception, although the connectome post I published last week also came up.

In this interview, my co-author on the nociception paper, Sakshi Puri, talks a bit about getting emails from PETA. When we published our paper, I blogged about my worries that there would be some people who would not like it regardless of what the paper actually says. I was disappointed to learn I was right, after the amount of effort we put into the paper to prevent misunderstandings.

For the record, if any of you have a problem with my research, please include me in that conversation.

There are 80 other interviews in this series. For fellow neuroethologists, some that might be particularly interesting include:

• David Perkel on bird song
• Karen Bales on primate bonding
• Peter Narins on acoustic communication
• Mike Smotherman on bat vocalizations
• Suzana Herculano-Houzel on comparative brain sizes
• Brenton Cooper on bird song development

Mine was so enjoyable and the questions were so good, I plan go back and listen to a lot of episodes in their back catalog.

UTSA talk

On Wednesday, I drove up to San Antonio to give a talk and meet the fine folks in the University of Texas San Antonio neuroscience group. Because I had decided to talk about nociception, Sakshi Puri came along with me. We got to San Antonio early enough Wednesday that we were able to play a little hooky, and decided that it was a lovely day to go to the zoo. We saw this massive guy there:

Biggest snapping turtle I have ever seen. It looked like it was a million years old.

Thursday went very well. We met lots of people who were doing interesting science but who weren’t waaaaay into themselves. My feature talk was well received, had a mini-Tweet-up (one person who was following me from the Ecology meeting last summer!), followed by lunch with students.

We then recorded an interview of Neuroscientists Talk Shop. My interview isn’t up yet; I’ll let you know when it it. But there are plenty of other interviews there for the neurocurious (76, I think). Just the thing to keep your mind working through an exercise routine, say! We talked about nociception and yesterday’s connectome post.

One of the unexpected things I learned on this trip from my host, Todd Troyer: How to catch a zebra finch.

If a zebra finch escapes in your room, wait until it lands. Note where it is. Then turn off the lights, and reach and grab where it was.

These guys completely shut down when the light goes out. In a room full of chattering birds, the silence was so sudden when we flipped the light switch out that it seemed as though the switch was connected to the birds and the lights both. I just couldn’t get over how immediate and complete the silence was, and how quickly they started up again when the lights went back on.

After the visits, we went to The Monterey Restaurant. The website does not at all convey the great, funky feeling of the place. It also features the most... different... desert I think I have ever had: the cheese-plate pop-tart. It’s a slightly surreal combination of sweetness and, well, cheese. I was glad that I had it, because it was a taste unlike any other I can ever remember experiencing. I’m not sure I would order it again.

Thanks to all the students and faculty at UTSA for making it such a fun day for us!

Overselling the connectome

In the last few years, there has been much discussion about the prospect of tracking the neural connections of mammalian, and particularly human, brains at very high levels of detail. Following the concept of a genome – every gene in an organism – a connectome is a map of every anatomical connection between every neuron in an organism.

One of the major proponents of this effort has been Sebastian Seung, who you can see giving a TED talk here. He sells the idea that understanding the human connectome will help us understand human identity. In his talk, Seung encourages his audience to say along with him. “I am my connectome.” He’s written a new book on this subject, Connectome: How the Brain’s Wiring Makes Us Who We Are.

This is an ambitious research project that will no doubt yield highly improved techniques to get anatomical information and analyze it. We will learn a lot from it.

And it will fail.

The allure, promise, and shortcomings of the connectome approach are yesterday’s news to neuroethologists. In the 1960s and 1970s, neuroethologists put in a lot of effort to crack partial connectomes of several species. These were usually referred to as “circuits” or “wiring diagrams.” (“Connectome” only appeared when neuroscientists got genome envy.) We made good progress on these. For example, we can explain escape behaviour in fishes and crayfish by the main synaptic connection between the critical neurons. That said, escape systems were chosen specifically because they were unusual behaviours. they are very sterotyped, very fast, and dedicated to one single task.

As other circuits were cracked, they revealed a much more subtle story.

A new paper by Bargmann details the case histories of a few of the species that neuroethologists have basically cracked the circuit. And contrary to some expectations, getting the complete set of synaptic connections did not solve the problems of understanding behaviour. I’m very glad that Bargmann wrote this paper, because it saves me the trouble of writing a much longer blog post.

For example, the nematode worm Caenorhabditis elegans has 302 neurons, and all the connections between them are known (the first complete connectome in the animal kingdom). Bargmann writes:

At a more profound level, however, the wiring diagram was and remains difficult to read. The neurons are heavily connected with each other, perhaps even overconnected – it is possible to chart a path from virtually any neuron to any other neuron in three synapses. ... Circuit studies suggest a reason for this failure: there is no one way to read the wiring diagram.

One of the major lessons that emerged in the 1990s from the study of these small circuits where we knew all the synaptic connections was the importance of neuromodulation. Neurons’ functions were not set only by their anatomical connections. They were profoundly influenced by a cocktail of neuroactive chemicals that could change the physiological responses of neurons.

Bargmann breaks it down. First, she shows that only rarely can you link single neurons to single behaviours. Then, she shows how one behaviour can result from several circuits, and how one neuromodulator can influence several behaviours. She notes that given how neuromodulation has appeared pretty much in every nervous system where we’ve looked, there’s every reason to expect it’s going to be a major factor in determining human neural activity, and thus, human identity.

In his TED talk, Seung draw an extended metaphor that the connectome is like the bed of a river.

I would like to propose a metaphor for the relationship between neural activity and connectivity. Neural activity is constantly changing. It's like the water of the stream; it never sits still. The connections of the brain's neural network determines the pathways along which neural activity flows. And so the connectome is like bed of the stream; but the metaphor is richer than that, because it's true that the stream bed guides the flow of the water, but over long timescales, the water also reshapes the bed of the stream. And as I told you just now, neural activity can change the connectome. And if you'll allow me to ascend to metaphorical heights, I will remind you that neural activity is the physical basis – or so neuroscientists think – of thoughts, feelings and perceptions. And so we might even speak of the stream of consciousness. Neural activity is its water, and the connectome is its bed.

Knowing the bed of the river still doesn’t tell you everything. The same river bed can have a trickle one day, and a flash flood the next. Neuromodulation is a bit like a dam partway along the river. It can regulate whether you have a torrent or a trickle.

Bargmann and I agree that connectome projects are very useful. But they alone will not solve the question of human identity. But at least when they fail, they will fail in an interesting way.

Reference

Bargmann C. 2012. Beyond the connectome: How neuromodulators shape neural circuits. BioEssays: In press. DOI: 10.1002/bies.201100185

Go Barsoom!

I am excited that Edgar Rice Burroughs’s John Carter of Mars is coming to the movie theatres*,  just in time for its hundredth anniversary.

While the story has a lot of trappings that we’ve come to associate with high fantasy (swords, princesses, and the like), I want to make the case that A Princess of Mars is truly science fiction. And despite that it’s early science fiction, and that scientific knowledge has moved on in the last century, Burroughs got something right. Indeed, it’s something that later, ostensibly more sophisticated science fiction tends to gloss over, particularly in film and television.

Gravity.

Mars, Burroughs reminds us, has lighter gravity than Earth. Lower gravity means that John Carter, a Virginia everyman, becomes stronger than he ever would be on Earth. (Later, Superman’s would repeat the twist, with Krypton and Earth substituting for Earth and Mars.) The scientific fact about this basic force of nature is woven into the warp and weft of the books, and is never forgotten.

In contrast, gravity is ignored in most popular science fiction. People walk around on spaceships in the middle of interstellar travel as though they were on a building, not in weightlessness.

Occasionally, you’ll hear some one-liner tossed off about “artificial gravity generators” or some such to explain this. This is a good time to remember that of the four fundamental forces we know in this universe – gravity, the strong nuclear force, and the weak nuclear force, and electromagnetism – we can only manipulate the last of those. Physicists are still betting on whether the Large Hadron Collider will finally reveal why things have mass.

I sympathize with filmmakers. Trying to simulate weightlessness is tricky, and requires complicates special effects. But I do wish that they would address it more often. And judging from the previews, I’m happy that the makers of John Carter have chosen to embrace this aspect of the story, and that it is given due credit as the science fiction pioneer that it is.

* This is despite Disney giving the film the most boring and nonevocative logo in memory. Akzidenz-Grotesk? This does not convey any of the familiarity of the turn of the Victoria era or the alien nature of the Martian landscape. And the title isn’t much better. Just John Carter? Not even John Carter of Mars?


Book cover from here, a great site that contains lots of information and artwork from many printings of the story. For me, Frank Frazetta’s interpretation of Barsoom is definitive.

Carnivals for March 2012

The Carnival of Evolution #45 is up at Splendour Awaits. The first slideshow in this carnival’s history, I think!

Circus of the Spineless #70 is at Beasts in a Populous City.

Tuesday Crustie: I’m not yellow... I just have yellow tips

Have no idea of the species of this crab, photographed in waters around New Guinea. I just love the yellow accents.

Photo by bbialek905 on Flickr; used under a Creative Commons license.

“Kids”

I get annoyed whenever I hear university instructors, either in person or online, referring to their students as “kids.”

It’s disparaging. It’s dismissive. It undervalues their abilities and undercuts their views.

University students are adults. They don’t deserve to be tagged as children any more.

(Exceptions will be made for any student who is a goat.)

The Zen of Presentations, Part 51: Redrawn

“This is so ugly.”

I have been preparing for my talk at the University of Texas San Antonio this week. For context and background, I wanted to include some graphs from other, previously published papers as well as my own stuff. There were two problems.

First, the quality of the graphs I wanted to use wasn’t always there. Many were old, pixelated images. Some graphs had unlabelled error bars, and some had text overlapping with error bars. Some bar graphs had hatching to distinguish the bars that was not very pleasing to look at.

Second, the style of the images I wanted to use varied wildly. Some were monochrome, some used colour. Some used serif types, some used sans serif type. The shape of the graphs sometimes didn’t come anywhere near the shape of the slide.

Even with my own material, I was pulling together images from several years and projects – manuscripts, conference posters, unpublished stuff – and I was painfully aware that it didn’t fit together very well. As I’ve written about before, consistency matters.

So I redrew everything.

With my own material, this was tedious but straightforward. I just had to locate a lot of archived files on my hard drive, opened them up, and started changing fonts, colours, and proportions.

Making other people’s stuff consistent can be trickier. First, I typically had to grab images. For PDF files, there is a snapshot tool in Adobe Reader that lets you do grabs of anything on the screen. It isn’t turned on in the toolbar by default, though. Click at right to enlarge.

Once I have a grab of the graphic, I can then put it into a full graphics editor (I’m a Corel Photo-Paint user myself; other software packages are available). For instance, I can get rid of text that I don’t need or remove the background. But even PowerPoint can do some basic manipulations quite well.

For some graphs, I need to go right back to ground zero and redraw the graph in my own software. There is a shareware program called Datathief that I’ve used to get extract information from published graphs so I can replot it. It’s fairly simple to use for distinct data points, like scatter plots or bar charts. I haven’t tried to extract a curve yet.

I have heard that data extraction from published graphs is possible in Matlab, though I haven’t done it myself.

In the end, almost every image in my presentation has been altered, tweaked, cropped, redrawn, recoloured, resized, or revised. It took a few solid days to do it. I am convinced it’s worth it, though. The level of harmony in the talk is so much higher, and the overall effect of the presentation is so much stronger, than if I had just left it looking like a scrappy quilt.

Related posts

The Zen of Presentations, Part 41: Consistency