A great way to get me to read your book is to include “-ome” in the title. I read most popular works on genomics and the growing body of books discussing the microbiome. Sebastian Seung’s book, “Connectome” is a timely discussion of the growing momentum in neurobiology. Neurobiology is an area of major investment in “big science” right now, with Obama administration announcing the “BRAIN” (Brain Research through Advancing Innovative Neurotechnologies) initiative in April of 2013. The “connectome” is the complete set of connections between neurons in an organism. As with other “omes”, the use of the term “connectome” is justified by a high degree of complexity but also by the sense that with the right tools and techniques, the subject can be defined in terms that will be useful.
Where popular works about genomics provide background introducing (or re-introducing) us to Watson and Crick and then the genome race between Frances Collins and Craig Ventner, this book introduces a less familiar cast to the reader. We meet Ramon Cajal who did early work in classifying neurons. We learn about Penfield’s early map of brain regions to senses. Recent technologies, especially functional magnetic resonance imaging (fMRI) as well as the intersection of genomics and neurobiology are introduced in an accessible manner. Because fMRI and other imaging technologies generate massive amounts of data, the need for high end computing platforms to support neurobiology research is discussed.
Seung argues that the “connectome” view of the brain and nervous system is the most likely to yield deep insights. Among the alternatives are a primarily structural perspective or a primarily gene/protein focus. The work performed with a relatively simple animal model, the worm Caenorhabditus elegans, provides an intriguing taste for how this could work. C. elegans has a finite number of total cells (959) and a finite number of neurons (302) and its genome has been fully sequenced. As an animal model, this allows informative research integrating imaging and genetic work. One of the major challenges for studying the human connectome is that there is not a fixed number of neurons in the human body. After reading this book, I remain unclear about what the ideal ultimate model of the human connectome will look like. It won’t be “neuron 5,540 in this patient lacks 2 of the 20 connections normally found to neuron 7,590”.
While I was initially troubled to see a sizable portion of the book dedicated to discussion of the feasibility mind transfers to computers (the “singularity”), two subsequent books that I’ve read after “Connectome” had dedicated discussion to this topic as well. One was a science fiction novel, where I still think that most discussion of mind-to-computer transfers belong, but the other was Al Gore’s “The Future”, in his chapter about emerging biological and medical trends.
This book provides a very accessible and useful introduction to both the classic experiments in neurobiology and emerging areas of inquiry. I recommend the book for its value as an overview and for its currency in covering technologies such as fMRI. While the book dedicates considerable discussion to the future of the analysis of the connectome, my lingering concern is that a clear description of the shape and form that a map of the connectome would assume is lacking. When the human genome project began, the state of the end result could be described fairly clearly. Paraphrasing, “we will begin at nucleotide 1 and end at position x (3 billion+) and will know if there is an ACG or T at every position in between. The first genomes completed will be the reference genomes and then individuals can be compared to these references.” While I am fully persuaded by Seung that there will be significant value in gaining increasingly deeper understanding of the connectome; I think the field would be helped by an even clearer sense of the structure of the “completed” state. The likelihood of a “reference connectome” is relatively low, given the anatomical deconstruction that would be required.
In his concluding remarks, Seung acknowledges that this lack of a clear goal is a key problem distinguishing neuroscience from genomics. Despite this concern, I found this book to be very helpful in expanding my knowledge and understanding of this high priority field.
