Author: jlolds

Native Angeleno, professor of Neuroscience and Public Policy at George Mason University

John Holdren on Fusion Energy

From ScienceInsider….

John Holdren, Obama’s science advisor, is actively supporting new investment in developing fusion energy as a carbon-free alternative source. He’s a fusion alum and so am I–just out of college, I interned for the New England congressional delegation looking at the possibility of developing fusion–the question then, as now, was containing a plasma efficiently. It’s not an easy nut to crack.
But if we were to crack it, it would really open up significant technological solution strategies to dealing with anthropogenic climate change.
Jim

How important is federal investment in science?


I’ve started many talks with remarks about FDR’s science advisor, Vennevar Bush, who in his report Science, The Endless Frontier, advocated forcefully for substantial federal investment in science R&D as a driver of the economy. In the present context of economic crisis, and in light of the Obama Administration’s very significant move towards funding science in the Recovery Act, now would be an excellent time to return to Bush’s thesis and attempt to generate data showing the relationship between federal investment in science and economic activity (as measured say by GDP). I’m particularly interested in whether it would be possible to tease out a causal relationship between the two–that is, does federal science R&D actually accelerate GDP growth and by what mechanism?

It seems to me that if a case could be made, one that uses recent data and that demonstrates some causality, that would be an extraordinarily powerful argument to bring before the US general public and their elected officials. It would also strongly buttress the new Administration’s policy moves to put science front and center of their agenda.
Who would fund such research? And how important would it really be?
Jim

Team science versus Single Investigator

Certainly across biosciences, a notable trend has been the lists of authors for single papers getting longer. This is especially true for the high impact journals and reflects the evolution of the practice of scientific research from individual investigator to large teams of scientists all working on various parts of a single question or problem. Part of this evolution is due to the need to use many methodologies to completely tell a single scientific “story” –in many cases considerably more techniques than any one single investigator can manage.

This team approach has been explicitly pushed in recent years, most saliently by the recently retired NIH director, Elias Zerhouni. There are some real problems however with the team approach. One of the most important is that maintaining quality control over the entire corpus of experiments that make up a team-authored paper becomes potentially challenging. An additional complication is that with large teams, who actually did what becomes opaque to the reviewer.
I’m not advocating a wholesale return to single PI science in biology–the subject matter has become too complex for many questions in the discipline. Rather, I’m urging a renewed appreciation for what can be accomplished in a single PI laboratory, where, in outstanding cases, a single creative mind can design an elegant set of experiments that like a fine gem, outshine the industrial output of large team labs.
Going further, it seems to me that with appropriate Science 2.0 sharing approaches, we may see a new renaissance of individual investigators re-using data produced by very large groups in imaginative ways that lead to real scientific progress.
Jim

Do we really just need to put more time on it?

On the way down to Wintergreen today we listened to more of Malcom Gladwell’s book, Outliers. The last chapter was perhaps the most interesting to me–about the KIP school in Bronx, where they get rid of summer vacation and essentially catch inner city kids up to their elite private school brethren, at least in mathematics. The notion is that while the rich kids go to summer camp and read, the poor kids just watch TV and play. They fall behind over the summer break. Apparently Korea and Japan don’t really have much of a summer vacation–which to Gladwell, explains their excellence at quantitative subjects entirely.

This is an attractive idea to me because it gets out the tired framework of nature versus nurture. Maybe it’s neither–it’s just getting, to use Gladwell’s term, your “10,000 hours” in.
There’s a case there for simple showing up and hard work. I like that.
Jim

DIADEM Challenge

The Krasnow Institute, HHMI and the Allen Institute for Brain Science announced a grand challenge project today–to create better tools for image analysis.

Money quote:

The organizers hope the DIADEM Challenge—short for Digital Reconstruction of Axonal and Dendritic Morphology—will lead to innovative solutions to a frustrating problem that has slowed efforts to create a functional atlas of the brain. Neuroscientists agree that a systematic characterization of neurons with their dendrites and axons is essential, since these tree-like structures are highly correlated with the electric activity of, and precise connections between, neurons and are thus linked to the functions of specific brain circuits. But scientists currently spend weeks—and, in some cases, months—tracing the intricate neuronal processes by hand, using data supplied by imaging studies.

Jim

More problems for BOLD

As many of you know, I worry deeply that functional MRI has been oversold. While recent papers have suggested that functional neuronal activity may occur without a concomitant BOLD signal, another critique suggests that the statistical techniques for analyzing fMRI themselves may be suspect:

Money quote from the neuroskeptic blog:

Just in case you need reminding of the story so far: A couple of months ago, MIT grad student Ed Vul and co-authors released a pre-publication manuscript, then titled Voodoo Correlations in Social Neuroscience. This paper reviewed the findings of a number of fMRI studies which reported linear correlations between regional brain activity and some kind of measure of personality. Vul et. al. argued that many (but by no means all) of these correlations were in fact erroneous, with the reported correlations being much higher than the true ones. Vul et. al. alleged that the problem arose due to a flaw in the statistical analysis used, the “non-independence error”. For my non-technical explanation of the issue, see my previous post, or go read the original paper (it really doesn’t require much knowledge of statistics).

Hat Tip to Marginal Revolution

Jim

Getting the Discussion Section right

As an editor of a scientific journal, I’ve had a long history of tending to focus on the Methods and Results Sections (especially the figures and their legends) at the expense of the Discussion Section and the Introduction. This in the context of the current way we organize scientific articles.

That said, I find myself facing the challenge of mentoring doctoral students in how to write a paper for publication. The difficulty is that even though I might discount the Discussion as an editor, still as an author, they do need to be written.
It is easy to communicate what not to do:
Don’t simply regurgitate the Results with the addition of speculative commentary and citations.
Don’t write a mini-Review paper–confusing that distinguished scientific form for the function of Discussion.
Don’t hype your results beyond what they clearly say. Especially avoid phrases like “to our knowledge, the present work represents the first….”
But what should go into a Discussion?
Seems to me that the biggest clue come from the word “discussion”.
Here are the dictionary definitions:
1. Consideration of a subject by a group; an earnest conversation.
2. A formal discourse on a topic; an exposition.
So let us take the first definition. Imagine a group that includes you, the author, and additionally your readers (including potentially your reviewers). The Discussion section should represent the consideration of the Results where your written words represent that complete consideration as if all the members of the group were in fact participants.
Hence, you might imagine the Discussion to represent the stylized representation of that group consideration were it to actually take place in a seminar room, complete with slides and pointed questions.
You present that familiar slide which summarizes your findings (each one corresponding to a result). Your audience members ask scientific questions (just as they would during a seminar) and you do your best to answer them. The above written into a Discussion section, amounts to a formalized discourse (the second definition from above)–but really amounts to just the imaginary “minutes” of what was presented and what was asked during our imaginary talk where you are presenting to the group (your readers).
Thus one ought to order the paragraphs of the Discussion section such that the most important finding goes first. Then it is put into context–why it is the most important finding. Most important is the implicit inclusion of what might be construed as reasonable scientific critiques on the finding (this is the inclusion of your imagined audience) along with your answers to those critiques. It is within this imagined give and take that appropriate referral to the relevant literature becomes important.
To do the above clearly requires both some sense of imagination based heavily in reality. You’ll write a better Discussion if you’ve actually presented your real data to a real audience!
And then on to the next most important finding.
The trick is to embody all of this “discussion” in your Discussion without it all sounding like the minutes of the local PTA meeting. Rather the “minutes” are transformed into a formal exposition (second definition).
One ends with a summing up of what the significance of the Results taken in their totality might mean to the field–with speculation kept to a real minimum.
Jim