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Human Connectome Project: the great controversy begins

December 6, 2010

This is one of those topics that is a *very* big deal…but for which it is going to be difficult to convey the import, owing to the technical involvement of the subject. Try to hang with me on this, though–I will do my best to make it digestible!

The necessary starting point is to understand the NIH’s push for a Human Connectome Project. The “connectome” refers to a yet-to-be-created map of the wiring connections in the human brain. This is a very big deal! I don’t think that I can overstate how essential this map will be for revolutionizing our understanding of phenomena such as human cognition and psychiatric disease. By comparison, the Human Connectome will be for neuroscience what the Human Genome is for molecular biology. And, like the Human Genome, the completion of the Human Connectome map will only be the beginning (and a darn-exciting beginning) to better unfolding the layered complexity we each carry within our skulls.

Steve Petersen at Washington University is the chair of the fMRI portion of the Human Connectome Project (hereafter “HCP”). The fMRI team has laid out a two-phase timeline for completion of the project: phase I will be a two-year period of selecting methodology; phase II will be dedicated to the acquisition and analysis of the brain imaging data. Over the five-year course of the project, brain scans will be acquired from over 1,000 participants, looking at their brains’ activity patterns during both resting states, and during engagement in cognitive or performance tasks. The overall strategy is thus: 1) to use task-related brain scans to identify functional networks in the brain, and 2) to use the resting-state data to determine the finer-scale connectivity between brain regions.

Enter Randy Buckner, stage left.

At the Society for Neuroscience meeting last month, Randy Buckner–a big player in the fMRI arena from Harvard University–had two posters from his laboratory that presented a direct challenge to the meticulous planning of the HCP investigators. The posters were entitled “Estimates of surface-based cortical networks using intrinsic functional connectivity from 1000 subjects” and “Estimates of cerebellar, thalamic and basal ganglia circuits using intrinsic functional connectivity from 1000 subjects.” The response from conference goers to the Buckner lab posters was quite dramatic. I overheard one scientist ask a colleague, “So, would you say that the Human Connectome Project just got scooped?” To which his companion replied, “No. I would say they just got their asses kicked to Tijuana.”

Randy Buckner’s lab–in contrast to the HCP plans–relied exclusively on resting-state data to create sweeping maps of connectivity within the human brain. They (quite impressively) imaged the brains of 1,000 subjects during an intense scanathon lasting only a few months. That is huge throughput of subjects.

The controversy, then, comes down to very critical questions about whether resting-state scans–that is, brain scans in which the subjects are in a neutral, wakeful state–provide the correct information by themselves about large-scale brain networks. It is an open question. (Well…it’s an open question depending on who you talk to.)

There’s a case to be made for both sides, I think. In the “resting-state-AND-task-engaged-scans” camp, a chief argument is that conclusions about the boundaries of functional networks are only meaningful when you are looking at data in which those networks are actively engaged. Just from my own research on the insula, I can attest firsthand to the fact that functional connectivity outcomes do indeed fluctuate when the subject is engaged in a cognitive task that draws upon a particular brain region, versus when the subject is only scanned during a wakeful-rest state. In the “resting-state-scans-ONLY” camp, the argument is that the markers of intrinsic network connectivity are preserved in the brain, regardless of the functional engagement of the subject; and to let the resting-state data speak for itself by using k-clustering algorithms to define candidate networks, rather than imposing network masks derived from the task-positive brain scans.

Steve Petersen will have an article in a forthcoming issue of the Annals of the New York Academy of Sciences, in which he will lay out the case for the necessary inclusion of task-related scans in order to create an accurate connectome map in humans. I look forward to reading the article, and to further understanding the case for the necessity of task scans in functional connectivity analysis.

At the end of the day, though, the final answer will be provided when the HCP completes its connectome map. At that point, team “task-AND-resting” and team “resting-ONLY” can compare notes, and hash out the explanations that underpin any differences in their results.

To further draw the parallels between the Human Connectome Project and the Human Genome Project, when the NIH announced the Human Genome Project, they announced that it would take a span of years (I believe their initial projections were 15 years?) to complete the sequencing. Then Craig Venter–a private interest maverick–entered the scene and said that he could complete the sequencing of the entire human genome in 18 months. The competition introduced by Venter created a major acceleration in the NIH sequencing project, and ultimately resulted in a joint announcement of the project’s completion by both Venter and the NIH.

As an optimistic take-home message, I think that the strong differences in opinion, and the subsequent competition that it introduces, will ultimately prove to be a strength working toward the purity of the science, even though it will be an ongoing source of consternation in the near future. It creates a charge that will be the power for an important dialectic on the topic. And, when all is said and done, having both the Harvard and the Wash U data sets with enormous quantities of information in each will allow us to ask important additional questions about the fundamental nature of the functional connectivity signals in the brain, and how they are affected between task engagement and default activity.


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  1. I think, like the Human Genome Project, when the Human Connectome Project finishes we will be surprised at how little it tells us about the brain.

    This is my impression, anyway, of the HGP. Everyone was so excited to finish it, but when you’re done all you have is a gene sequence. The human body is so much more complex than just the sequence. It includes the current state of the sequence (genes being on or off, for example), as well as non-genetic information like types and timings of hormones from the mother.

    And yet the completion of the genome project is a vital base of information for a *whole bunch of stuff*. The amount of important research that is possible because of the completion of the HGP is staggering.

    I expect that the same will be true of the Human Connectome Project. When it is done we may be surprised at how little we still know about the brain, yet it will be a vital, necessary base on which to build research that just isn’t possible at this point.

    It’s exciting. Thanks for sharing, Michael.

    • permalink

      Buraianto, I think you are spot-on with your assessment. Simply having the connectivity map will not be inherently useful. But it will be foundational for extending basic understanding of the brain as a mechanical system, as well as leading to important discoveries about neural and psychiatric abnormalities. The completion of the HCP will be a beginning point…not an ending point.

  2. J Harris permalink

    I admire your optimistic take-home message.

    On the other hand, brain imaging studies are *really* expensive, and to see public funds spent on partly-redundant experiments by two separate groups of scientists… it just doesn’t sit very well.

    To what extent do you think the ego might be a factor here?

    From a practical standpoint, couldn’t this controversy be addressed with a single 1000-person experiment that included both resting-state and task-engaged-state data? Make the data available to researchers on each side of the controversy, have them analyze it with their own algorithms, compare and contrast conclusions.

    Of course we can benefit from a healthy debate on this subject, but no need to replicate experiments.

    • permalink

      Hi Janna. I understand your concerns about the allocation of public funding to partially-redundant experiments. Personally, I hope that bioinformatics in general will ultimately transition toward open source libraries for researchers to investigate. It *is* inefficient for every research team to accumulate their own pool of subject information de novo when they could perform complementary analyses on data sets already existent (e.g., brain connectivity data from imaging, whole-genome sequencing data, microarray expression profiles, etc.). Especially when–as you note–resources *are* limited, there is definitely a better way. I think it would be safe to attribute some of the resistance to open source bioinformatics to ego-driven territorialism.

  3. dorothy deasy permalink

    Isn’t the ability to repeat and get the same results (or not) the heart of the scientific method?

    • permalink

      That’s a good point, Dorothy. I think this is particularly true at the front end of any new development. It would be a much greater source of waste in the long run to build years’ worth of follow-up studies on a platform of information that was later discovered to have discrepancies with a cross-check data group.

  4. I also doubt whether the sum total of the data to be acquired in the HCP will compete with what can be achieved quite easily through pooled efforts such as the 1000 Functional Connectomes. Indeed, adding a resting-state fMRI (rs-fMRI) scan to a task-based experiment takes just a few minutes, and the acquisition parameters can be standardized based on what we know today. A single site/scanner is never going to be able to collect the amount and diversity of rs-fMRI scans than can be obtained over the hundreds of research MRI centers worldwide.

    But, there is an important caveat. For me (disclaimer – I’m an MRI physicist) the most important part of HCP is the technical development, not the data acquisition per se. HCP is funding the development of hardware (a custom 3 T) and sequences that simply wouldn’t have happened by 2012 via conventional funding mechanisms. NIH is providing “venture capital” that will catalyze the ability of the neuroimaging community to acquire advanced connectivity data. Some of these developments will require a new scanner, some will require just a new pulse sequence. The net result will be that whatever connectivity data is collected using today’s technology (which is actually methods/hardware that are years old now) and which resides in today’s databases, will be updated/replaced in the next few years with richer data sets than we have now. HCP will be the first to offer these new, richer data sets by virtue of the fact that they will be the first group capable of the new methods. At which point the interesting question is then whether or not there are fundamental differences between these new data sets and those already resident in the Harvard databases and elsewhere. We shall have to see. We can guess at answers today, but they are pure speculation.

    (Okay, I’ll bite and speculate. Since I happen to know that the diffusion data will most definitely be better in the HCP custom scanner, there’s every chance the white matter connectivity data will be more accurate. Further, HCP has “go faster” fMRI sequences coming online that may allow sampling at sub-second rates for whole brain. This may reveal interesting temporal dynamics as networks come on and off that simply aren’t detectable at the 2 sec TR rates that are common today. Thus, my bet is that either HCP itself, or the technical developments it spawns, will radically change the richness of connectivity data in the future.)

    • permalink

      I appreciate your comments, practiCalfMRI. This is valuable perspective re: the spectrum of advances we can anticipate from the HCP. Thanks for joining the conversation, and welcome!

  5. Peter Schuller permalink

    I am not a neuroscientist but follow developments in connection with my work and have always taken a “complex adaptive system” approach to understanding the brain’s functionality, so I agree that this is a great start, in a long, long journey.
    On a related subject, I saw your tweet about “disease memes” and am curious about your thoughts on that subject, given how memes may very well drive many of our “unconscious thoughts”, all of which can alter brain structure and functionality. (I believe in the theory that epigenetic mechanics can cause thoughts and self-reflective behaviors to alter brain structure.)

    • permalink

      Hi, Peter. What a fascinating topic you bring to attention. I don’t have a *whole* lot of informed commentary on this topic as of yet, although it is certainly a topic of interest to me. More research has definitely been done of the causal affects of biology on cognition than has been done to elucidate the causal relationship of cognition on biology. There are some good studies that pioneer the latter exploration, though. The “Healing Emotions” and “Destructive Emotions” series sort of chips away toward this domain. Also Sharon Begley’s compendium “Train Your Mind, Change Your Brain” is a good base text for a personal study of plasticity. I invite you to keep a communication channel open, and to let me know of exciting thoughts and finds!

      • Peter Schuller permalink

        Thanks, Michael. Yes, I know of Begley’s work (enjoy her writing on a variety of science topics). As you suggest, it does seem that most of the work in this emerging issue of cognitive effect on brain biology and structure deals with emotions, which obviously have their own category of neurodynamics. It will be interesting to see how the research plays out. I do not currently have a lab or a budget for this type of research, and while over the long term there may be huge benefits generated from meme-gene co-evolution research, it seems that not many labs today will find it “practical” (read, immediate benefit) enough to focus on it.

  6. permalink

    …it seems that not many labs today will find it “practical” (read, immediate benefit) enough to focus on it.

    Where are the rich eccentric pot-stirrers when you need them? 🙂

    Incidentally, I have a list of interesting projects I would like to fund if I somehow manage to become independently wealthy. Wouldn’t that be nice? Lol.

  7. Peter Schuller permalink

    I will certainly let you know if I find one of those eccentric pot-stirrers…and if you do hear of anyone who is working on the epigenetics of causal relationships between cognition and biology, please do let me know.

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