Connectome Read Free Page A

averages over populations. The sizes of the brain and its regions remain almost useless for predicting the mental properties of an individual.
    This limitation is no mere technicality. It is fundamental. Although phrenology assigns functions to brain regions, it does not attempt to explain
how
each region performs its function. Without that, we cannot explain in a satisfying way why the region might function especially well in some people and malfunction in others. We can, and must, find a less superficial answer than size.
    In Part II, I introduce an alternative to phrenology called
connectionism,
which also dates back to the nineteenth century. This approach is conceptually more ambitious, because it attempts to explain how regions of the brain actually work. Connectionists view a brain region not as an elementary unit but as a complex network composed of a large number of neurons. The connections of the network are organized so that its neurons can collectively generate the intricate patterns of activity that underlie our perceptions and thoughts. The organization of connections can be altered by experience, which allows us to learn and remember. The organization is also shaped by genes, as described in Part III, so that genetic influences on the mind can also be explained. These ideas may sound powerful, but there is a catch: They have never been subjected to conclusive experimental tests. Connectionism, despite its intellectual appeal, has never managed to become real science, because neuroscientists have lacked good techniques for mapping the connections between neurons.
    In a nutshell, neuroscience has been saddled with a dilemma: The ideas of phrenology can be empirically tested but are simplistic. Connectionism is far more sophisticated, but its ideas cannot be evaluated experimentally. How do we break out of this impasse? The answer is to find connectomes and learn how to use them.
    In Part IV, I explore how this will be done. We are already starting to develop technologies for finding connectomes, and I’ll describe the cutting-edge machines that will soon be hard at work in labs around the world. Once we find connectomes, what will we do with them? First, we’ll use them to carve the brain into regions, aiding the work of neo-phrenologists. And we’ll divide the enormous number of neurons into types, much as botanists classify trees into species. This will dovetail with the genomic approach to neuroscience, because genes exert much of their influence on the brain by controlling how neuron types wire up with each other.
    Connectomes are like vast books written in letters that we barely see, in a language that we do not yet comprehend. Once our technologies make the writing visible, the next challenge will be to understand what it means. We’ll learn to decode what is written in connectomes by attempting to read memories from them. This endeavor will at long last provide a conclusive test of connectionist theories.
    But it won’t be enough to find a single connectome. We will want to find many connectomes and compare them, to understand why one mind differs from another, and why a single mind changes over time. We’ll hunt for
connectopathies,
abnormal patterns of neural connectivity that might underlie mental disorders such as autism and schizophrenia. And we’ll look for the effects of learning on connectomes.
    Armed with this knowledge, we will develop new methods of changing connectomes. The most effective way at present is the traditional one: training our behaviors and thoughts. But learning regimens will become more powerful when supplemented by molecular interventions that promote the four R’s of connectome change.
    The new science of connectomics will not be established overnight. Today we can only see the beginning of the road, and the many barriers that lie in the way. Nevertheless, over the coming decades, the march of our technologies and the understanding that they