… or at the very least, how pop science works!
A lot of people believe some version of the ‘chemical soup’ story. I wrote an essay about it a few years ago: The Chemical Self and the Social Self.
… or at the very least, how pop science works!
A lot of people believe some version of the ‘chemical soup’ story. I wrote an essay about it a few years ago: The Chemical Self and the Social Self.
My latest 3QD essay is about the mystery of human memory, and why it is not at all like computer memory. I discuss the quirks of human memory formation and recall, and the concept of “content-addressable memory”.
Here is an excerpt:
Decades of experience with electronics has led many people to think of memory as a matter of placing digital files in memory slots. It then seems natural to wonder about storage and deletion, capacity in bytes, and whether we can download information into the brain ‘directly’, as in the Matrix movies.
The computer metaphor may seem cutting edge, but its essence may be as old as civilization it is the latest iteration of the “inscription metaphor”. Plato, for example, described memory in terms of impressions on wax-tablets — the hard drives of the era. According to the inscription metaphor, when we remember something, we etch a representation of it in a physical medium — like carvings on rock or ink on paper. Each memory is then understood as a discrete entity with a specific location in space. In the case of human beings, this space is between the ears. Some memory researchers even use the term “engram” to refer to the neural counterpart of a specific memory, further reifying the engraving metaphor.
Before getting to the problems with the inscription metaphor, I should say that at a sufficiently fuzzy level of abstraction, it is not entirely useless. There is plenty of neuroscientific evidence that memories are tied to particular brain regions; damage to these regions can weaken or eliminate specific memories. So the general concepts of physical storage and localizability are the least controversial aspect of the inscription metaphor (at least at first glance).
The issue with the inscription metaphor is that it leaves out the aspects of human memory that are arguably the most interesting and mysterious — how we acquire memories and how we evoke them. When we look more closely at how humans form and recall memories, we may even find that the storage and localizability ideas need to be revised.
Read the whole piece here:
I was asked the following question on Quora:
Why is planning & decision making situated in the frontal lobe?
Here’s my answer:
Why not? 🙂
I suppose the most obvious answer is the fact that the motor cortex resides in the frontal cortex.
Now you may justifiably ask: what does the motor cortex have to do with planning and decision-making?
The connection is this: to a large extent, the purpose of the brain is to control the body. So planning and decision-making, at the simplest possible level, involves determining when and how to move the body.
From this perspective, it is interesting to speculate that all thoughts derive from the process of virtual or simulated movement. Thought arises in the ‘gap’ between perception and action.
The way an organism interacts with its environment can be understood in terms of the perception-action loop.
Stimuli from the outside world enter the brain through the sensory organs and percolate through the various brain regions, allowing the organism to form neural ‘representations’ or ‘maps’ of the world. Signals originating inside the body (such as from the stomach or the lungs) allow for similar maps of the inner world of the organism.
By using memory to compare past experience with present conditions, an organism can anticipate the future to meet its current needs: either by acting in the present, or by planning an action for some future time.
The signals that control our voluntary muscles emanate from the motor cortex: the neurons in this part of the brain are the ‘switches’, ‘levers’ and ‘buttons’ that allow us to change our body position and configuration.
So going back one more step, the signals that influence the motor cortex constitute the ‘proximal’ decision signal. Much of the input to motor cortex comes from premotor and prefrontal areas, which are nearby in the frontal lobe. The thalamus also sends important signals to motor cortex, as do the neuromodulatory systems (which include the dopamine, acetylcholine, norepinephrine and serotonin systems).
Ultimately you can keep going ‘back’ to see how every part of the brain influences the ultimate decision: sensation, memory and emotion all play a role. But the prefrontal and premotor areas constitute the most easily identifiable decision areas.
As to why these brain areas are located in the frontal lobe at all… this is a much more difficult question. The short answer is evolution by natural selection. But the long answer is still incomplete. Brains are soft tissue, so they don’t leave fossils.
Interesting interview in the Atlantic with cognitive scientist Donald D. Hoffman:
“I call it conscious realism: Objective reality is just conscious agents, just points of view. Interestingly, I can take two conscious agents and have them interact, and the mathematical structure of that interaction also satisfies the definition of a conscious agent. This mathematics is telling me something. I can take two minds, and they can generate a new, unified single mind. Here’s a concrete example. We have two hemispheres in our brain. But when you do a split-brain operation, a complete transection of the corpus callosum, you get clear evidence of two separate consciousnesses. Before that slicing happened, it seemed there was a single unified consciousness. So it’s not implausible that there is a single conscious agent. And yet it’s also the case that there are two conscious agents there, and you can see that when they’re split. I didn’t expect that, the mathematics forced me to recognize this. It suggests that I can take separate observers, put them together and create new observers, and keep doing this ad infinitum. It’s conscious agents all the way down.”
Here’s the striking thing about that. I can pull the W out of the model and stick a conscious agent in its place and get a circuit of conscious agents. In fact, you can have whole networks of arbitrary complexity. And that’s the world.
“As a conscious realist, I am postulating conscious experiences as ontological primitives, the most basic ingredients of the world. I’m claiming that experiences are the real coin of the realm. The experiences of everyday life—my real feeling of a headache, my real taste of chocolate—that really is the ultimate nature of reality.”
I don’t agree with everything in the article (especially the quantum stuff) but I think many people interested in consciousness and metaphysics will find plenty of food for thought here:
Also, the “conscious agents all the way down” is the exact position I was criticizing in a recent 3QD essay:
The diagram above is from a science fiction story I was working on, back when I was a callow youth. It closely related to the idea of a network of conscious agents. Here’s another ‘version’ of it.
Not sure why I made it look so morbid. 🙂
I was asked this question on Quora recently:
The brain has neurons which approximately perform function evaluations on their inputs. How would this cause brainwaves of different frequencies? Why are they related to the level of arousal in the brain (sleep/meditation etc)?
Is there some sort of “controller” that synchronizes the firing?
This is an excellent set of questions!
1. Why does the brain have waves?
There is no consensus on their functional role, but some researchers think oscillations facilitate flexible coordination and communication among neurons.
2. The brain has neurons which can approximately be understood as performing function evaluations on their inputs, though the actual mechanisms are more complex. But how would this cause brainwaves of different frequencies to exist?
There are several possible mechanisms that can cause the input-output transformation of neurons to lead to oscillations when the neurons are connected in networks. Furthermore, neurons themselves often have intrinsic oscillatory properties (other than basic spiking), such as rebound excitation following inhibition.
3. Is there some sort of “controller” that synchronizes the firing?
There is no single controller causing synchronization or oscillation — there are actually several local and meso-scale mechanisms, often involving inhibitory interneurons*. (Note that synchronization and oscillation are distinct phenomena. You can have synchronized non-oscillatory processes, and oscillations that are not synch-ed.)
What are brain waves?
Even though we use the generic term ‘brain waves’, there are actually a variety of distinct mechanisms at work that lead to rhythmic behavior in different frequency bands. And in many cases we still don’t know what the mechanism is that causes a particular brain rhythm, or can’t decide among multiple plausible mechanisms.
Even though I’m a computational neuroscientist, I find it hard to conceptually integrate all the different perspectives on neural activity. But I’ve been thinking about this a lot lately, so here goes!
The most fine-grained perspective involves measuring the voltage of an individual neuron. This voltage can change in various ways. The most well known is the spike, or action potential. Spikes travel efficiently down the axon, and typically cause vesicle release in the synapse, which allows neurotransmitters to affect the post-synaptic neuron. But spiking is not the only kind of voltage fluctuation in a neuron. There are also ‘sub-threshold’ fluctuations, which are often oscillatory. These oscillations may represent oscillatory and/or synchronized inputs to the neuron that are insufficient to cause spiking. Single-electrode and multi-electrode recordings of cell activities can pick up both the sub-threshold fluctuations and the supra-threshold spiking.
Brain waves were first discovered through electroencephalography (EEG), which has been around for a century or so. Unlike electrode-based recording, EEG is non-invasive (meaning we don’t have to poke any sharp objects into anyone). But the main drawback of EEG is that it is a coarse-grained measure of neural activity. It measures the cumulative electrical activity of very large numbers of neurons.
It’s also important to realize that EEG essentially measures the synchronized inputs to a brain area, rather than the firing outputs. This has to do with the biophysics of the technique, which you can read about in more detail in my answer to the question “Are EEG voltages related to the average action potential firing rate of the cortical neurons near the electrode or are the voltages the average of low frequency voltage oscillations of the neurons?” EEG effectively measures the degree of synchronization of neurons that send inputs to the brain region directly underneath the EEG electrode.
Brain rhythms tend to be grouped into frequency bands. The most well-studied bands have been assigned Greek letters that reflect the order of their discovery. Here’s a list of the bands, along with their frequency ranges in hertz (Hz). I’ve linked to their Wikipedia pages, when available.
What are the mechanisms that cause brain waves?
Through a combination of experimental techniques and theoretical approaches, neuroscientists have come up with several mechanisms that can explain oscillations in various frequency bands. In many cases it is not clear which mechanism is in fact at work.
I can’t really go though all the theoretical mechanisms that have been proposed, but I can talk about one that is very intuitive to understand: the PING model of Gamma activity. This model, developed by Nancy Kopell, has been widely corroborated by experimental work. (There may be different types of Gamma, however, and not all of them are covered by this model.)
PING stands for pyramidal-interneuronal network gamma, and involves interaction between excitatory cells and inhibitory cells, resulting in the creation of a nonlinear oscillator. The following diagram  illustrates the mechanism quite nicely:
The E(xcitatory) cells excite the I(nhibitory) cells, which in turn inhibit the same excitatory cells. This results in an oscillation whose frequency is determined by the rate of integration of the I-cells. Fast I-cells can produce fast rhythms.
There are plenty of other mechanisms for oscillations, but the PING model will give you a flavor of how they can be constructed. Arousal levels can by incorporated into models by incorporating factors such as neurotransmitter level fluctuations, and the effects of such fluctuation on the sub-threshold and/or firing properties of neurons. Changes in behavioral state can also change the inputs to various brain areas from the body and from the outside world, which in turn will affect the network activity mode. This is a vast topic for theory and computational modeling.
What is the purpose of brain waves?
This is actually still a very contentious issue. The field of neuroscience can be broadly divided into researchers who care about oscillations, and researchers who don’t. People who don’t care about oscillations are more interested in the firing activities and the input-output transformations of neurons and networks. Some of these researcher even go so far as to claim that oscillations are ‘epiphenomena’ — mere side-effects of the ‘main’ neural processes, such as integration, contrast enhancement, switching, resetting, and so on. I was broadly in the ‘skeptics’ category for many years, but I’ve started to realized that oscillations can’t be ignored. The power in various frequency bands often correlates strongly with behavioral measures, so oscillations are at the very least telling us something important about how the brain works.
One theory of brain waves that is becoming popular is the idea of coordination, or “communication through coherence”. The idea is that neurons which are in the same sub-threshold oscillatory state are more likely to be able to communicate spikes with each other. This is shown diagrammatically below . The black neuron is out of phase with the blue neuron, so it communicates with the blue neuron less effectively that the red neuron.
As I mentioned earlier, synchrony and rhythmicity are completely distinct. Presumably you can get coherence without any rhythms, just by synchronizing groups of neurons. But maybe rhythmic behavior is more easy to control.
I’ve only scratched the surface of this topic. There is definitely a lot more to the story of brain waves, and in the coming decades hopefully researchers will work towards an integrated theory.
A recent Quora answer I wrote:
I was asked the question “From a scientific point of view, how are our tastes created?” Here’s my answer.
“There’s no accounting for taste!”
Typically we explain taste — in food, music, movies, art — in terms of culture, upbringing, and sheer chance. In recent years there have been several attempts to explain taste from biological perspectives: either neuroscience or evolutionary psychology. In my opinion these types of explanations are vague enough to always sound true, but they rarely contain enough detail to account for the specific tastes of individuals or groups. Still, there’s much food for thought in these scientific proto-theories of taste and aesthetics.
Let’s look at the evolutionary approach first. An evolutionary explanation of taste assumes that human preferences arise from natural selection. We like salt and sugar and fat, according to this logic, because it was beneficial for our ancestors to seek out foods with these tastes. We like landscape scenes involving greenery and water bodies because such landscapes were promising environments for our wandering ancestors. This line of thinking is true as far as it goes, but it doesn’t go that far. After all, there are plenty of people who don’t much care for deep-fried salty-sweet foods. And many people who take art seriously quickly tire of clichéd landscape paintings.
Evolutionary psychology can provide broad explanations for why humans as a species tend to like certain things more than others, but it really provides us with no map for navigating differences in taste between individuals and groups. (These obvious, glaring limitations of evolutionary psychology have not prevented the emergence of a cottage industry of pop science books that explain everything humans do as consequences of the incidents and accidents that befell our progenitor apes on the savannahs of Africa.)
Explanations involving the neural and cognitive sciences get closer to what we are really after — an explanation of differences in taste — but not by much. Neuroscientific explanations are essentially half way between cultural theories and evolutionary theories. We like things because the ‘pleasure centers’ in our brains ‘light up’ when we encounter them. And the pleasure centers are shaped by experience (on the time scale of a person’s life), and by natural selection (on the time scale of the species). Whatever we inherit because of natural selection is presumably common to all humans, so differences in taste must be traced to differences in experience, which become manifest in the brain as differences in neural connectivity and activity. If your parents played the Beatles for you as a child, and conveyed their pleasure to you, then associative learning might cause the synapses in your brain that link sound patterns with emotional reactions to be gradually modified, so that playing ‘Hey Jude’ now triggers a cascade of neural events that generate the subjective feeling of enjoyment.
But there is so much more to the story of enjoyment. Not everyone likes their parents’ music. In English-speaking countries there is a decades-old stereotype of the teenager who seeks out music to piss off his or her parents. And many of us have a friend who insists on listening to music that no one else seems to have heard of. What is the neural basis of this fascinating phenomenon?
We must now enter extremely speculative territory. One of the most thought-provoking ‘theories’ of aesthetics that I have come across was proposed by a machine learning researcher named Jürgen Schmidhuber. He has a provocative way of summing up his theory: Interestingness is the first derivative of beauty.
What he means is that we are not simply drawn to things that are beautiful or pleasurable. We are also drawn to things that are interesting: things that somehow intrigue us and capture our attention. These things, according to Schmidhuber, entice us with the possibility of enhancing our categories of experience. In his framework, humans and animals are constantly seeking to understand the environment, and in order to do this, they must be drawn to the edge of what they already know. Experiences that are already fully understood offer no opportunity for new learning. Experiences that are completely beyond comprehension are similarly useless. But experiences that are in the sweet spot of interestingness are not boringly familiar — but they are not bafflingly alien either. By seeking out experiences in this ‘border territory’, we expand our horizons, gaining a new understanding of the world.
For example, I’m a Beatles fan, but I don’t listen to the Beatles that often. I am, however, intrigued by music that is ‘Beatlesque’: such music can lead me in new directions, and also reflect back on the Beatles, giving me a deeper appreciation of their music.
The basic intuition of this theory is well-supported by research in animals and humans. Animals all have some baseline level of curiosity. Lab rats will thoroughly investigate a new object introduced into their cages. Novelty seems to have a gravitational pull for organisms.
But again, there are differences even in this tendency. Some people are perfectly content to eat the same foods over and over again, or listen to the same songs or artists. At the other extreme we find the freaks, the hipsters, the critics, the obsessives, and all the assorted avant garde seekers of “the Shock of the New”.
Linking back to evolutionary speculation, all we can really say is that even the desire for novelty is a variable trait in human populations. (Actually it’s multiple traits: I am far more adventurous when it comes to music than food.) Perhaps a healthy society needs its ‘conservatives’ and its ‘progressives’ in the domain of taste and aesthetic experience. Group selection — natural selection operating on tribes, societies and cultures — is still somewhat controversial in mainstream evolutionary biology, so to go any further in our theories of taste we have to be willing to wander on the wild fringes of scientific thought…
… those fringes are, after all, where everything interesting happens! 🙂
For more speculation on interestingness, beauty, and the pull of the not-completely-familiar, see this essay I wrote. I go into more detail about Schmidhuber’s theory about interestingness:
From Cell Membranes to Computational Aesthetics: On the Importance of Boundaries in Life and Art
This has nothing to do with science, but I find this David Mitchell video on taste very funny:
After writing this answer I realized that the questioner was most probably asking about gustation — meaning, the sense of taste. Oh well.