A central thesis of the book is that biology does not work like physics, and even less so like engineering. Biological systems are not easily reducible to separate units that, when put together, give us the whole back
This thinking reflects a mapping between structure (anatomy) and function (behavior) that goes back more than a century.
one of the central approaches of neuroscience has been a divide-and-conquer strategy that tries to break up the entire organ into subcomponents that can be, purportedly, properly understood. They then can be put back together in the hope that the overall functionality will reflect the summed individual parts. I believe this strategy is problematic; in fact, it is inadequate to understand systems like the brain (and genetics by the way) in which the interactions among the parts create mechanisms and processes than cannot be derived by looking at parts in isolation
We don’t have to put functions inside little boxes in the brain and tell neat stories. Reality is immensely more complex
The view formulated here is that parts of the brain work in a coordinated fashion, such that functions are carried out by large-scale distributed circuits, also called large-scale networks. In other words, collections of gray matter parts exchange signals with one another and, by doing so, bring about behaviors. The circuits are distributed, not local, involving disparate parts in the cortex and the subcortex, for example. And they are “large scale” because they don’t only involve a pair, or possibly a few regions, but many components working simultaneously. That is the sense in which the brain is entangled
Many lay readers (and some neuroscientists) implicitly assume that the human brain is rather unique with its prominent cortex
However, in the past several decades, neuroanatomists have uncovered striking similarities in the overall “plan” of the brain of all vertebrates (fish, amphibians, reptiles, birds, and mammals
one notion that is the outcome of my research over the past 30 years—and that undergirds the entire text—is that perception, cognition, action, emotion, and cognition are closely interrelated in the brain. You can’t point to the brain and say, “This is where X happens.”
This book makes the case that because the brain is not a modular system, we need conceptual tools that can help us decipher how highly entangled, complex systems function
The notion of an area/region is at the core of neuroscience as a discipline, with its central challenge of unraveling how behaviors originate from cellular matter. Put another way, how does function (manifested externally by behaviors) relate to structure (such as different neuron types and their arrangement)?
this approach also exposes a seemingly insurmountable chicken-and-egg problem: If we don’t
Historically, two winners in the search for rightful units have been the neuron and the individual brain area
The seemingly benign question—what counts as an area?—is far from straightforward. For instance, is the amygdala one region or 12 regions? This region is far from an esoteric case. All subcortical areas have multiple subdivisions, and some have boundaries that are more like fuzzy zones than clearly defined lines
Science as a discipline is inextricably associated with understanding entities in terms of a set of constituent subparts. Neuroscience has struggled with this modus operandi since its early days, and debates about “localizationism” versus “connectionism”—how local or how interconnected brain mechanisms are—have always been at the core of the discipline. By and large, a fairly modular view has prevailed in neuroscience. Fueled by a reductionistic drive that has served science well, most investigators have formulated the study of the brain as a problem of dissecting the multitude of “sub-organs” that make it up
We’ll discuss neural networks again in chapter 8, but here we emphasize their conceptual orientation: thinking of a system in terms of collective computation.
Neuroscience seeks to answer the following central question: How does the brain generate behavior?6
Although neuroscience studies are incredibly diverse, one way to summarize them is as follows: “Area or circuit X is involved in behavior Y”
The examples above weren’t gratuitous; all were important studies published in very respected scientific journals. Although these were rigorous experimental studies, they don’t quite inform about the underlying mechanisms.7 In fact, if one combs the peer-reviewed literature, one finds a plethora of filler terms8—words like “contributes,” “involved,” and “enhances” above (figure 1.2)—that stand in for the processes we presume did the “real” work. This is because, by and large, neuroscience studies don’t sufficiently determine, or even strongly constrain, the underlying mechanisms that link brain to behavior.
typical explanation about combustion motors in automobiles will invoke pistons, fuel, or controlled explosions. It will not discuss these phenomena in term of particle physics, for instance; it won’t invoke electrons, protons, or neutrons
How much do we know about the brain today?
In reality, we know rather little.
We can predict whether a car is moving or not, and how fast it is moving, by “imaging” its speedometer. That does not mean that we understand how an automobile works. It just means that we’ve found something that we can measure that is strongly correlated with an aspect of its function. Just as with the speedometer, imaging [measuring] activity in the amygdala (or anywhere else in the brain), in the absence of further knowledge, tells us nothing about the causal mechanism and only provides a “marker” that may be correlated with an emotion.
The “explanation” above works because it provides a causal narrative: a series of cause-and-effect steps that slowly but surely lead to the outcome
Contrast such state of affairs to the vision encapsulated by Isaac Newton’s statement that “truth is ever to be found in simplicity, and not in the multiplicity and confusion of things” (Mazzocchi 2008, 10).12 This stance is such an integral part of the canon of science as to constitute a form of First Commandment
The present book embraces a different way of thinking, one that revolves around ideas of “collective phenomena,” ideas of networks, and ideas about complexity. The book is as much about what we know about the brain as it is a text to stimulate how we can think about the brain as a highly complex network—indeed entangled—system.
We’ll see that action flexibility necessitates uncoupling sensory and motor components
Because the concept of function is so central to our discussion, chapter 4 is entirely devoted to unpacking the idea
A comment on the word “entangled” in the book title, which conjures multiple interrelated ideas. What I roughly want to convey by using it is not something like threads that are mixed together but can be separated if only one has enough time and patience. The meaning I want to convey is closer to “integrated,” but single words do not do justice to the general theme permeating the book
In humans and some other mammals, the cortex is not smooth but highly convoluted; if spread like a dough, it would be the size of a large pizza, so the invaginations help pack a larger brain inside the skull
Although at first glance the cortex looks the same everywhere, in some sectors it may have as few as three and in others as many as six discernible cell layers
and the thickness of the cortex is not the same everywhere but varies between two and three millimeters
Despite the complexity revealed by slicing brain tissue, the brain’s organization can be better appreciated if we consider how is forms embryologically. The entirety of the organ originates from a structure called the neural tube, which is literally shaped like a cylinder. At some point during embryonic development, this tube, which is fairly regular at first, creases at three places and bulges so that four compartments can be discerned (figure 2.3). These are the forebrain (front brain), midbrain (middle brain), hindbrain (back brain), and spinal cord. The last three contain no cortex; the first contains both the cortex and several subcortical structures, which we’ll learn about later
the rightmost sector gives rise to all forebrain regions, including the entire cortex, and all subcortical structures above the midbrain.
Two other parts of the cortex are not visible from the outside and need to be seen from the inside to reveal themselves: the cingulate (see figure 6.1), which lies along the middle part of each hemisphere (the brain is made up of two halves, or hemispheres), and the insula (see figure 6.6), which is hidden by the “lid” of the frontal and parietal cortices
Although we often associate the cortex with the human brain, this type of tissue is present in all mammals
In a basic sense, what makes the cortex “cortex” is that it contains a laminated pattern
Cécile and Oskar Vogt, and Brodmann working separately in their lab, were part of a first wave of anatomists trying to establish a map of the cerebral cortex. Neurons are diverse, and several cell classes can be determined based on both shape and size. Researchers used these properties, as well as spatial differences in distribution and density, to define the boundaries between potential sectors. In this manner, Brodmann subdivided the cortex into approximately 50 regions per hemisphere.3 The Vogts, in contrast, thought that there might be over 200 of them, each with its own distinguishing cytoarchitectonic pattern (that is, cell-related organization). Brodmann’s map is the one that caught on and stuck, and today students and researchers alike still refer to cortical parts by invoking his map.
There is a deep logic to what the Vogts and Brodmann were following. In fact, it is an idea that comes close to being an axiom in biology: Function is tied to structure such that, in the case at hand, parts of the cortex that are structurally different (contain different cell types, cell arrangements, cell density, and so on) carry out different
functions
In a stunning paper published in 1936, Alan Turing devised an imaginary machine that was capable of calculating anything that can be algorithmically computed! This was, of course, before any hardware computer was ever constructed
The ideas by Turing, as well as those by the mathematicians Alonzo Church, Kurt Gödel (among the all-time most significant logicians), and John von Neumann (famous for designing the basic logic architecture of modern computers), among many others, had a profound effect on philosophers and scientists trying to understand the notion of “computation” in both natural systems (including the nervous system) and artificial ones
An influential framework to emerge in the new field called “philosophy
of mind” was that of functionalism, which asserts that mental states are identified by their functional role—not by how they are physically implemented. Thus, a “mind” can be instantiated by various physical systems, possibly even computers, as long as they carry out appropriate computations. According to functionalism, the human brain is one of possibly many physical devices capable of implementing mental functions. In theory, at least.
For vision, audition, somatosensation, and taste, individual pathways carrying signals from the sensory periphery pass through the thalamus before reaching the respective cortical areas
But the thalamus is much more than a simple “relay station” for sensory information reaching the cortex. Anatomists subdivide it into more than 10 subregions with complex connectivity patterns with both the cortex and a very rich array of subcortical regions. Indeed, in later chapters, we will discuss how the thalamus is critically involved in cortical-subcortical loops that play essential computational roles.
A remarkable property of the striatum is that, with the exception of the primary visual cortex, all of the cortex projects to it, from sensory regions with simple responses to frontal areas that participate in abstract processes
In humans, below the forebrain, the central nervous system extends downward into the midbrain, hindbrain, and spinal cord. The brainstem frequently refers to the large collection of structures in the midbrain and hindbrain
Given that the brainstem is relatively large, it is typically subdivided into three sectors: the midbrain itself, in addition to the pons and medulla in the hindbrain
The brainstem is the home of many circuits essential for basic processes, such as breathing and controlling heart rate—in short, the regulation of life. In fact, damage to the upper brainstem can cause coma and the so-called persistent vegetative state of partial arousal but not true awareness, in which patients can open their eyelids occasionally and exhibit sleep-wake cycles but completely lack cognitive function
what prevents undampened excitation? Neurons influence each other not only in an excitatory fashion but also through inhibition. In the latter case, when a neuron fires, it makes the neurons connected to it less likely to generate an action potential.
Neurotransmitters are very diverse (around 100 different molecules have been cataloged), but approximately 10 of them do most of the heavy lifting. They go by names such as dopamine, serotonin, acetylcholine, histamine, and so on, some of which are even household names
It is quite humbling that we don’t really know how SSRIs work; the mechanisms of action are not well understood. Like many medical treatments, they were discovered by accident, and physicians prescribe them for depression and anxiety based on clinical experience. Ralph Adolphs and David Anderson go as far as suggesting that “trying to cure these [depressed] patients without understanding how the brain generates an emotion state would be like trying to cure the bubonic plague in the fifteenth century without understanding that bacteria and viruses cause infectious disease”
What the associationists were hinting at can be viewed as an early incarnation of “network theories.” In a nutshell, brain functions are not carried out by single, isolated regions but by coalitions of regions that may be involved in neural circuits that are not local—for instance, involving parts of parietal and frontal cortex in the case of speech and language.
it? In this chapter, we describe the idea of a hypothetical “minimal brain” that allows an animal to defend itself and seek rewards, essential components of survival
a brain can be thought of as an entire circuit “in between” sensory and motor cells
This “solution” frees animals from acting simply based on sensory stimulation
It turns out that there was a second visual system lurking underneath the cortex all along
We now know that residual vision is present in persons with a lesion to the primary visual cortex. They may detect the abrupt appearance of objects, movement, and several other visual properties
The reasons behind patients’ abilities are yet to be completely worked out, but much depends on two small hills in the midbrain at the top of the brainstem. The two structures, one on each side, are called the superior colliculus (where “colliculus” is small hill in Latin).3 (The superior colliculus is very close to the area called PAG in figure 2.2.)
Previously, we discussed how the cortex is comprised of layered sheets of neurons and the subcortex is poorly structured. In biology, “rules” always have exceptions, and though part of the brainstem, the superior colliculus is beautifully layered
Retinal projections to the superior colliculus are topographic, meaning that the spatial layout of light hitting the eye (left/right, up/down) and triggering retinal responses is preserved in the colliculus
Input-output arrangements, pretty much necessary for survival, are implemented by the nervous systems of the simplest organisms and, remarkably, can be accomplished by even a single sensorimotor cell
the single-celled solution is rather inflexible, of course: Pretty much every time the receptor senses something, the effector does its job. The solution, though costly, is to grow more cells in the “middle.” And that is what nature did when given a few hundred million years.
we can think of the brain, with all its different parts
as evolution’s solution to the problem of uncoupling inputs from outputs
How is a stimulus classified as harmless, which may or may not be worth investigating further, as opposed to constituting an emergency that requires immediate action? The stimulus’s position in the visual field plays an important role here. In small rodents, unexpected movement overhead (much like that of a predator) more likely triggers flight, whereas movement in the lower field (possibly a prey) more commonly elicits approach (figure 3.4). Thus, the superior colliculus could implement a rule much like this: If movement is overhead, flee; otherwise, if movement is in the lower field, consider further exploration.
The optic tectum of the lamprey contains five stacks of neurons. As in other vertebrates, the superficial layers receive optic fibers, and the deep layers send outputs that contribute to movements.
Take the brain of the simplest groups of presently living vertebrates: lampreys, which are water inhabitants with elongated, eel-like bodies, and hagfish, sometimes referred to as slime eels. These animals are important to study because they provide clues about characters that were present in the common ancestor to all vertebrates.
Though intuitive, this observation reflects a fundamental principle of brain function—context sensitivity. The brain does not simply react to sensory stimuli; instead, incoming data are incorporated into ongoing processing that encompasses the states of the brain and the body, explaining why the exact same stimulus exerts very different effects depending on the situation: in one setting a stimulus may lead to inquisitive approach, in another to moving away
The PAG is where outputs from the superior colliculus (and many other brain regions) can be processed into more full-blown defensive programs. In several ways, the PAG can be viewed as an extension of the deep layers of the superior colliculus
In a rat or a cat, excitation of neurons in the “active” column generates behaviors such as facing and backing away or a full-blown flight reaction, and these are very similar to natural actions seen when the animal is threatened or attacked. Excitation of neurons in the “passive” column generates an entirely different response—namely, the cessation of ongoing activity and profound hyporeactivity, with the animal neither orienting nor responding to its environment. This type of freezing behavior is rather similar to that of an animal that has incurred an injury or after defeat in a social encounter
The reason the pathway from the superior colliculus to the substantia nigra is particularly noteworthy is that the latter synthesizes and uses the neurotransmitter dopamine. Dopamine, by its turn, plays a significant role in the functions of the striatum, where dopaminergic processing (that is, cellular mechanisms that use dopamine as a key neurotransmitter for neuronal signaling and communication) is important during the processing of novel or salient stimuli. Dopamine has received enormous attention because of its involvement during reward processing, including approaching objects previously associated with liked foods.
A peculiarity of several neurotransmitters is that they are synthesized in only a handful of areas. Yet they punch way above their weight because the areas that produce them reach large swaths of the brain through their extensive anatomical connections—what we call “projections systems.
It is not too surprising, therefore, that dopamine is at times treated almost like a “reward molecule.” This infelicitous interpretation is common in the general media and in nonspecialty books. Unfortunately, it is also how some neuroscientists speak. But there is no such a thing as a “reward molecule”—the message is not in the molecule
dopamine is not a “reward molecule” for the same reasons we wouldn’t call it a “movement molecule” (given the motoric impairments seen in Parkinson’s patients).
The success of chlorpromazine and other more effective drugs (like haloperidol) led researchers to the “dopamine theory” of schizophrenia (Crow 1980): Drugs that have therapeutic effectiveness (they have antipsychotic effects) antagonize dopamine action. According to this framework, dopaminergic projections from the midbrain to the cortex and subcortical structures is overactivated in schizophrenia, dumping too much of this neurotransmitter in the recipient territories
Broca concluded his short case report published in the Bulletin de la Société Anthropologique, a mere page and a half in length, with the following momentous conclusion: “All this permits, however, the belief that, in the present case, the lesion of the frontal lobe was the cause of the loss of speech.” More than 150 years later, Broca’s report is the most important paper in the history of brain function localization.