This book examines the history of brain science through the lens of the different metaphors we’ve used over time to understand the brain.
The first half of the book is a cultural and scientific history of how we used to think about the brain. We used to think it was a collection of cavities through which “animal spirits” flowed. Then it became a machine, and there was the idea that if you took it apart, you could understand it just as we do any other machine. A century later, electricity was very fashionable, so there was the idea that the brain was full of electrical liquid, like a galvanic battery. By the mid 19th century, nerves were being described in detail, and they were compared to telegraph wires. We also see the rise of phrenology, which put forward the notion that brain functions are localized to specific modules in the brain, which has turned out to be partially true. Modern neuroscience begins in about 1950 according to Cobb, and that leads into the second part of the book, the present state of brain science. In this section, he highlights innovations such as brain imaging, detailed study of neurotransmitters, and optogenetics. Recently, the idea of the brain as a computer has been a major metaphor, and Cobb thinks it might be doing more harm than good, “by holding tightly to metaphors, we end up limiting what and how we can think.”
For most of our past we have viewed the heart, not the brain, as the fundamental organ of thought and feeling. Localization of forces was not always the dominant method, traditional Chinese approaches to medicine and anatomy were primarily focused on the interactions of a series of forces, rather than localization of function. Between 600 and 250 BCE, Greek philosophers began shaping what would become the modern view of many things, including the brain. Hippocrates advanced the idea that the brain is the seat of experience, but many others, such as Aristotle, still thought it was the heart. A few hundred years later, Galen demonstrated that the brain was necessary for consciousness, but not the heart, by cutting open live animals and putting pressure on the respective organs. There was also an idea that hydraulic pressure might move impulses around the body, but stimulating exposed nerves produced an almost instantaneous contraction of the connected muscle, so that idea fell out of favor. But there was still an idea that matter and motion cannot think, because then every atom would be a separate animal, and there was no fundamental difference between humans and machines. Also, parallels between humans and machines were generally considered to be highly immoral, because they were seen as questioning free will. If human choices somehow flowed from an underlying material process, rather than the spirit, then morality would collapse.
In 1791, Galvani discovered that electricity stimulated nerves to contract muscles, and concluded that there was some kind of innate electricity in the nerves. Later, Aldani, through continuous current from a battery, showed that electricity could produce life-like coordinated behaviors in dead animals.
Later, lesion studies, like those of Broca, showed that focal lesions could lead to quite specific cognitive deficits. Cajal, using a Golgi stain, found that nerves were discrete units, not a continuous net. The basic properties of neurons were discovered (set threshold for firing, refractory period, and set amplitude of firing).
McCulloch and Pitts showed that True/False statements, in conjunction with the basic operations AND, OR and NOT, enable the computation of arithmetic, setting the stage for the brain as a computational organ.
Penfield’s surgeries showed that stimulating parts of the cortex triggered the retrieval of very specific memories, advancing localization of function to memory as well. Single cell recording in rats also revealed that the hippocampus seemed to contain a detailed spatial map of the world. Kandel’s work in sea slugs elucidated some of the molecular building blocks of memory.
Cobb describes the rise of artificial intelligence, and criticizes the field for not producing insights that can be applied to biological pattern recognition systems. He says, “in general these astonishing computer programs do not produce clear biological hypotheses, and as a result they have shed little light on how real brains work.”
Cobb thinks the future of neuroscience lies in investigating simple (insect) brains at a very fine-grained level, which will lay the groundwork for understanding more complex brains.
What we don’t know:
Cobb maintains throughout the book that while we’ve discovered lots of stuff about the brain, we haven’t figured out some of its most fundamental functions: namely how the brain leads to subjective experience (why are we conscious at all?) as well as basic computational principles.
“There are many scientists who feel we are drowning in a tide of data about the structure of brains, while what we really need are some clearer theories and ideas about how it all fits together. As the pioneer neuroscientist Vernon Mountcastle put it in 1998: ‘in and of itself knowledge of structure provides no direct understanding of dynamic function. Where is not how.’”
Thought questions:
- Cobb criticizes fMRI at length in the book “A map-and at their best that is what fMRI data are-does not tell you how something works. Where is not how. The next time you read a claim that a particular ability, or emotion, or concept has been localised to a particular region of the human brain using fMRI, ask yourself, ‘So what?’” Do you think that’s fair?
Mather et al., 2013 has the following to say on the topic: “But to say that neuroimaging answers only “where” questions is to confuse the superficial format of raw neuroimaging data with the content of the questions those data can answer; Neuroimagers collecting fMRI data need no more restrict themselves to “where” questions than cognitive psychologists measuring reaction times need limit themselves to “when” questions.”
“Indeed, looking back over the past two decades of work using fMRI, one can see that an initial focus on “brain mapping” provided a critical foundation for the field that allowed it to go beyond “where” questions to address “how” questions. To the extent that highly specialized brain regions are discovered, and their functional specialization well established, activity in these regions can serve as markers for specific cognitive functions, enabling us to ask whether and to what extent mental process X is engaged in task Y. For example, by showing people a series of scenes and faces and asking them to remember one type of stimuli and ignore the other during a retention interval, researchers tested the hypothesis that people suppress mental representations of distracting to-be-ignored stimuli.”
- Cobb seems to set up a lot of straw men: “Just because a particular cell is activated by a photo of Jennifer Aniston does not mean that is all the cell does-other faces, or other stimuli entirely, may also be represented-or that cells from no other network are involved.” Did you think so too?
The original authors of the “Jennifer Aniston cell” paper (Quiroga et al., 2005) clearly state that “We do not mean to imply the existence of single neurons coding uniquely for discrete percepts for several reasons: first, some of these units responded to pictures of more than one individual or object; second, given the limited duration of our recording sessions, we can only explore a tiny portion of stimulus space; and third, the fact that we can discover in this short time some images - such as photographs of Jennifer Aniston - that drive the cells suggests that each cell might represent more than one class of images.”
- Cobb criticizes neural networks for not informing us about how the brain really works. Is that valid?
Many in that field believe that these models can help us generate mechanistic hypotheses about how computation might be carried out in the brain.
- Cobb says that the current metaphor of brain as computer is flawed, because it makes us think of it as a passive input output machine: “By viewing the brain as a computer that passively responds to inputs and processes data, we forget that it is an active organ, part of a body that is intervening in the world, and which has an evolutionary past that has shaped its structure and function. This view of the brain has been outlined by the Hungarian neuroscientist György Buzsáki in his recent book The Brain from Inside Out. According to Buzsáki, the brain is not simply passively absorbing stimuli and representing them through a neural code, but rather is actively searching through alternative possibilities to test various options. His conclusion - following scientists going back to the 19th century - is that the brain does not represent information: it constructs it.” Do you think this is a fair criticism?
- Did you think the book was organized around metaphors of the brain over time? What do you think the next metaphor will be?