Beyond Medicine, How Being Simply Scientific Keeps Me Stable

I’m a huge fan of science. So much so that I study it as a subject of philosophy as well as reading things like the Feynman Lectures for fun. Science is a part of my life. Some would call it a religion, in that I “believe in” science. That is, that I believe that it holds all the answers. Short answer to that is that I do not believe it holds all the answers. In fact, most any scientist that you ask that question to will provide the same answer, science is incomplete.

But it is not the end product of science that I hold on to. Which is where the religion question gets things wrong, as do other critiques. The current product of science has the possibility of error always built into it. It could be wrong. Now that might seem to be a problem in itself, and then warrants skepticism about science, but thinking that way would be wrong too. Just because something can be wrong, doesn’t mean that it is wrong. Nor does the possibility of something being wrong warrant skepticism in the opposite direction. One must have grounds for being skeptical.

So what does this have to do with moods, and in particular, psychosis? A lot actually. Obviously, we turn to science for meds to help with our mood swings and psychosis. It’s not a precise science, but it works well enough to get the job done. It has in my case. But we can also use the systematizing nature of science to our advantage. Plotting moods along many different points and charting them to gauge how well a drug is doing and how fast is it working. I need to form a new charting system, but the old one works well enough. But what it does is transform what is a bundle of subjective feelings into a more precise and organizable data set that we can look back on and see if progress has been made in the right way. It’s not rocket science. In fact, it’s done automatically by google charts and spreadsheets. But it’s turning a scientific eye to what is going on in my head and keeping track of the things that I care about. It’s also a recognition that my memory is faulty and remembering subjective moods when you are no longer in them is difficult. It’s the escape from the subjective to the objective, and that is part of what a scientific enterprise is about.

The skepticism and scientific format also helps with things like paranoia. I often get paranoid thoughts when my meds are getting low. I’ve written about them before, but they are mainly cabals of individuals working against me or trying to harm me. These thoughts pop up like a flash and I instantly believe them. It’s taken practice to even identify when these thoughts happen. The way to deal with them is quite scientific. It’s an element of Cognitive Behavioral Therapy to identify the thought, then ask whether you have evidence for it, then whether there are alternative explanations, and finally whether one does not know. After going through these three things, it’s fairly easy to dismiss the thoughts. Yet, it’s a very scientific approach to psychosis. All that’s being done is hypothesis testing. There is nothing fancy about alleviating paranoia, other than simple hypothesis testing and the right medication.

It still goes deeper than this. And a lot of people do it without thinking about it. But there is a strong distrust of one’s own subjective feelings. For me, it could be in a mood state and I have to distrust my reactions to things. Or it could be a psychotic state and I have to distrust my own thoughts. Finally, I put a significant amount of trust in other people to tell me what to do, e.g. my psychiatrist, girlfriend, and parents. Part of being scientific in one’s enterprise is not believing everything that comes in. In fact, that’s very dangerous for those of us who are mentally ill. Yet, remote corroboration is always necessary in scientific testing. It’s old fashioned, but it’s a corner stone.

It actually irks me when I talk with other people who are rather new age-y and believe that the subjective experience is everything. It completely neglects the reality of mental illness, where that is not a privilege. Rather, it’s the opposite. Without thinking that hard about it, we rely heavily on other people to live properly and function as a normal(ish) human being.

This does not mean that we immediately reduce to a materialistic metaphysics, but it does suggest that practicing simple scientific steps has plenty to offer in terms of remaining stable. It’s not hard to do these things, and it’s probably rather obvious once they’re pointed out. But just because it’s obvious after the fact doesn’t mean it’s not going on or shouldn’t be continued or honed into something better. And personally, knowing that I’m mentally ill, I know that I cannot take the world at first glance. I always need to be skeptical of what is going on and whether something in my brain is influencing me in a certain direction. This could be said of everyone, but the general populous isn’t concerned with equalizing their mood cycle like I am. Maybe it’s a perverted gift that I’ve been given to know how my brain is influencing me in certain directions; but I know it, and I control it through simple scientific operations.

But, Science IS Beautiful

I have a lot of irritations that get under my skin. One of them is ethical vegetarians wanting mined diamonds which probably cost people their lives. But another is the idea that mathematical and scientific knowledge devalues beauty. I personally know this to be false. In my mixed episodes, where I experience many things as beautiful, I find things that are mathematically complex and scientifically understandable to be incredibly beautiful. While individually interesting, the fact that they resonate in certain commonalities with everything else is beautiful in itself. As Carl Sagan said, we are all star dust. What is more beautiful than that?

I think that the harsh reaction to science and mathematics is because it removes individuality and mystery. By reducing an experience to a complex mathematical equation, it also means that it often follows simple rules that are reproducible. No experience is wholly unique and instead it is one that can be recreated by our own means if we had the right technological capabilities. As such, something unique and precious can become artificial. For instance, we can take the beauty of a diamond and recreate it in a factory. And mind you, synthetic diamonds are free from flaws, unlike mined ones. In a sense, they are perfect diamonds that follow every possible rotation and symmetry that their crystalline structure can have.

In that sense, the divide between uniqueness and artificial becomes involved. That some how nature is unique and precious, but our creations are just imitations. But to me, this is the wrong way to view the difference between what man makes and what nature makes. It sets mankind apart from nature, when we are a part of it. And nature is not unlike us. Nature is a grand mathematician. There are laws and fractals that infect every element of nature. It is utilized in many varied ways. And nature is a massive factory. Absorbing the basic materials from the soil and using them to build its own skyscrapers. It does so using simple processes too, which makes it all the more elegant in its constructions.

The artificial-natural divide also stems from an old philosophy of mind-body dualism. It is the idea that the human mind is something alien and not natural. This has a host of problems, particularly the explanation of how something that is not part of the natural world can interact with the natural world. We even see this idea today with various spiritualities, where the mind is some how infinitely complex and special. Not something reducible to science. But, being bipolar, I’m usually on the side that it is a material thing that we understand to a limited extent (we’ve only been at it for 30 odd years), otherwise my meds probably wouldn’t work so well.

The individuality and artificiality idea is really just one of a frame of mind. Where one views the world as not artificial or individual, but full of commonalities and not that different from our own endeavors. The only difference is that we are consciously doing things.

But the mystery angle is not just one of a frame of mind, but one of desires. When we look out on a landscape, there is an element of wonderment and mystery about it. It seems beyond comprehension that slow moving ice flows could carve such a sight. There is mystery to it because we cannot comprehend it. And this mystery drives us in many ways. Some of us seek to unravel the mystery like a puzzle. But we can also be content with just trying to fathom it in its totality. The mystery of nature is powerful in this respect because of how imposing it is in its complexity.

Science and mathematics appear to unravel this. After all, they explain the mystery. Understanding a magic trick often makes it far less interesting (to some people). And unraveling nature’s threads can have the same effect, it removes that mysterious unfathomability. Yet, a painter who knows the technicalities of a painting can still enjoy its beauty. So can a naturalist enjoy nature and find it wonderful and beautiful. I find that this is because a different sense of beauty has come over the technically proficient. Before, with mystery and incomprehensibility, there is a sense of ignorance involved. The aesthetic experience is triggered by unknowability. Wonderment comes from not knowing and with it a sort of reverence.

But this appears to me to be an almost childish thing to hold on to. To hold on to ignorance because one finds it beautiful. This is especially true when science can furnish a new sense of beauty. The world is not a magic trick to wonder at. It is complex and intricate. Without science and mathematics, we cannot fully see this complexity. But with it, the world grows in its complex nature and we often find ourselves in awe at brilliant complexity. As an astronomy novice, I understand the principles in play to keep the planets in orbit and their origins along with how the light bends so that I can view them. But, this does not reduce how beautiful the planets are. Along with seeing how beautiful the planets are, the sight embeds me in a historical narrative that stretches billions of years. While I used to view things as beautiful and wonder at them, now I experience a wonderful place in the world. I can glimpse at the ebb and flow of the world and how small and insignificant we can be. A beautiful landscape can be pretty to look at, but knowledge of the world around us can make us look inwards as well as outwards. It is a deep and beautiful experience to have. Science and mathematics can unlock this type of experience in the way that only knowledge can.

Earth From the ISS

Here’s something you might like, it’s earth from the point of view of the international space station. The movie is awe inspiring.

 

Confirmation of Scientific Theories

My primary focus is in scientific confirmation. So I thought I would share several theories about confirmation of scientific theories; they are Bayesian, Likelihoodism, Popperian, and my own Differential Confirmation.

All but the Popperian theory of confirmation revolve around probability, and Karl Popper even started to concede that his view is reducible to some degree of probability. So I’ll start off with a crash course in bayesianism.

Bayesianism gets its name from Bayes’ theorem, a mathematical theorem of probability. To understand this theorem, there are 4 important things to keep track of. First is the posterior probability of a hypothesis given an observation. This is written as P(H|O). Often, in bayesianism, this is what it means to confirm a hypothesis from a given observation. To calculate this, three other values are needed, the likelihood of a given piece of evidence given a hypothesis P(E|H), the prior probability of a hypothesis P(H), and the probability of the evidence P(E). These are related by Bayes’ Theorem: P(H|E)=P(E|H)P(H)/P(E)

To show how these work, let’s have the hypothesis that a particular card drawn randomly from a deck of cards is the ace of spades. So H is “this card is the ace of spades”, and let the observation E, be that the card is black. Now to start entering values.

Prior to the observation, the chance of a card being the ace of spades is 1/52. So P(H)=1/52. The probability of a card being black randomly drawn is 1/2, since half are black and the other half are red. Finally, P(E|H)=1, this is because being an ace of spades entails that it is black, so it gets the maximum probability assignable. According to Bayes’ Theorem, the result is that the probability of this card being the ace of spades is 1/52*1 / 1/2 = 1/26. And this is in line with our intuition that there are 26 possible cards and one of them will be the ace of spades. It works! After all, it’s math, it better work. Additionally, we say that the hypothesis is confirmed because P(H|E)>P(E). Disconfirmation is when the inequality goes the other way, and we have no confirmation when they are equal to one another. In the above card case, we see that 1/26>1/52, so our hypothesis is incrementally confirmed.

So now we come to confirmation of theories. We think of scientific hypotheses as being H, observations as E, and the likelihood as being what we think of as the hypothesis’ prediction. For now, I’ll ignore the problems with filling in some of these values, as it’s very hard in some cases.

Bayesianism councils us to adopt a theory whenever its posterior is above .5. This is because .5 is often the cut off for belief versus agnosticism. Why .5? It’s because P(H) + P(not H) = 1. So in cases of where the value is .5, then P(H) = P(not H), so we cannot decide between the two of them based on probabilities (assuming of course that our degree of belief in a theory should be determined by the probabilities of the theory).

The problems with this are threefold. First is that .5 is arbitrary. There why should we believe a theory to be true just because it’s marginally above .5. Why not some really high probability like .9, so we are really sure that it’s true. Secondly, it does not capture the problems of incremental changes to theories. This is because it’s a law of mathematics that if a new theory, with some additional hypotheses about the way the world works entails an old theory, then P(new theory|E)<=P(old theory|E). So no matter how many novel predictions that the new theory makes, it cannot be more probable than the old theory. Thus, why should we ever believe in an incrementally new theory? We shouldn’t on the bayesian account. Thirdly, what if we only have 2 theories and their posteriors are low? We should still select one or the other, shouldn’t we? What if general relativity’s prior is awfully low, so it’s posterior is never very high, none the less, it makes good predictions, so shouldn’t we still believe it to be true to some extent?

This is where likelihoodism attempts to solve the problems. It’s contrastive, meaning that it only works in comparing two theories. It works by having H1 and H2, as our hypotheses and examines what predictions it makes. In terms of confirmation, all we are interested in are the likelihoods. So all we look at is whether P(E|H1)>P(E|H2). It’s satisfying in that confirmation is only based on predictions. But this suffers from the problem of conspiracies. Conspiracies make the same predictions as a standard scientific hypothesis, so there is no difference between a conspiracy’s confirmation and a real scientific confirmation. Something else needs to be added to make sure that a hypothesis is a good scientific one. And this cannot be based in mathematics.

So what makes a good scientific hypothesis? Karl Popper introduced his own theory which is sticking one’s neck out. A good hypothesis that is confirmed to a greater degree than another is one that makes lots of bold new predictions. General Relativity made for a good hypothesis because it made the bold prediction that if one takes two atomic clocks, and one is flown around the earth at a high speed, then when comparing the two, they will not match up. Additionally, it made the prediction that if I see two lightning bolts striking at the same time, you might not see them striking at the same time. These are bold claims over and above what Newtonian mechanics predicted, so it’s a good hypothesis to be tested. And since these claims came out to be true, we should prefer GR over Newtonian mechanics. However, while this gives some claim to what makes a good hypothesis, Popper only said that one can falsify hypotheses through observation, never confirm. So we never believe a theory to be true, we just say that it isn’t falsified, yet.

My view is that science is concerned with what is confirmed to a greater degree. So rather than focusing on P(H|E), we look at P(E|H)-P(H). We select theories based on which is can be confirmed to a greater degree rather than which has the higher posterior. It’s contrastive so we choose theories over other theories, like likelihoodism. But we also solve the problem of conspiracies and new theories, and arbitrary points of belief. Plus, it’s rather Popperian in nature because a theory that makes a bolder prediction will enjoy a greater degree of confirmation. It takes about another 10 pages to explain all how it solves all of this, but it does work. I’m excited about my project since it captures incremental theory modification. The only concern that I have is that priors show up.

The major problem with priors I’ll leave as a puzzle. How does one figure out the prior probability of general relativity without any evidence? No one’s figured it out, so if you can, publish it. But this is a problem that’s inherited from bayesianism, so at the very least I can push it back on them. But it still concerns me considerably.

Schizophrenia and Bipolar Disorder – The Same in the Brain?

It’s old news in terms of the 24 hour news cycle, but I came across an article about brain scans between people with schizophrenia and bipolar disorder. Interestingly enough, in terms of how they appear in the brain, they work in a similar fashion around the hippocampus area. Specifically in the CA 2 and the CA 3 areas.

What does the hippocampus do then? And what are the CAs (cornu ammonis regions)? Primarily, the hippocampus is involved in memory with the CAs as the specific subregions of it. But it does not deal with motor skills or cognitive skills like playing a musical instrument. Rather, one of the roles is in detecting novel events, places, and stimuli (VanElzakker 2008). Its role also includes encoding stimuli in environmental contexts. So what this means is that in terms of interacting with environments, individuals with bipolar disorder and schizophrenia both see novel events in a similar fashion. Personally, I find this a fascinating result since it appears that to some degree, individuals with bipolar disorder and schizophrenia not only see the world in a similar way, but also view it differently from normal people. Perhaps this explains the environmental sensitivity found in both disorders, perhaps it doesn’t. But the findings are there and are interesting none the less. Additionally, since the hippocampus is also involved in long term memory, the reduced size of the hippocampus might explain the memory problems associated with both bipolar disorder and schizophrenia.

However, the similarities do not extend that far. In a study conducted in scanning the grey and white matter of the brains of individuals with schizophrenia and psychotic bipolar disorder, there were few similarities found. In a BJPsych publication, in schizophrenic individuals, there were reductions in grey matter of the temporal lobes, the neocortex, thalmus, and white matter in the cerebellum. These areas are involved in attention, language, emotional regulation, and conscious thought. The only similarities found were in the white matter, the cerebellum, which is involved in emotional regulation.

Furthermore, in a recent UCLA study, researchers found an overlap in genetic markers for bipolar disorder and schizophrenia. Of the 7 genetic markers found in schizophrenia, researchers found an overlap of 3 genetic loci between bipolar disorder and schizophrenia.

What these results demonstrate is that there is a fair amount of overlap between these two diseases. This might be enough to explain why medications for both are so similar. Yet, there are marked differences between the diseases, even between psychotic bipolar individuals and schizophrenia. With these differences, it means that the different classification of the two diseases is well founded, even though there is strong overlap between the DSM IV classification of both conditions with psychotic symptoms. While this is all fairly technical, I do find it an interesting result. I often associated psychotic symptoms of bipolar disorder and schizophrenia as being identical or very similar in some way. Rather, there is a general result that the two disorders are caused in the same way, but present different models in the brain. So there you have it, a crash course in the differences between bipolar disorder and schizophrenia. They seem similar, and they are to some degree, but primarily in the response to new environmental cues and emotional regulation. After that, even the psychotic symptoms differ in their presentation in the brain.

Raven’s Paradox and Hypothetical-Deductivism

I’m on a science kick lately, if you can’t tell by the last few posts. I’ve gotten my phil science batteries recharged with my current course and I feel like sharing more of what I do with the world. So today I’m going to talk about the hypothetical-deductivism model of science and the raven’s paradox. Technical words, but not that scary. What hypothetical-deductivism (from now on HD since I’m too lazy to write it out again) is, is a model for how science confirms and disconfirms hypotheses. It’s an old model, but it’s been updated to what is now called bayesianism, which I find suffers from similar problems.

So what is HD? It’s a logical approach that has two parts, confirmation and disconfirmation. Confirmation happens when we have an hypothesis that logically implies some observation. The hypothesis that all ravens are black entails that if x is a raven, then x is black. If we find something that is a raven and is black, then this confirms that all ravens are black. It can be much more interesting than this, but it’s mainly a common sensical approach to confirmation. If an hypothesis logically entails a prediction, and that prediction is correct, then the hypothesis is confirmed. Hence the name Hypothetical-Deductivism, one deduces observations from a hypothesis and if those observations are correct, confirmation happens, yay!

Disconfirmation happens in just the opposite way, that if it entails that an observation will not happen, but it does, then the theory is disconfirmed. So when Newtonian mechanics predicted that light from stars will not bend around the gravitational field of the sun (gravitational lensing), and then we observed that it did, it disconfirmed Newtonian mechanics while confirming general relativity.

It’s a straight forward approach that came out of a time when we thought that logic could solve all of our problems. It hasn’t, and it won’t. Why is this? Two reasons: white shoes and bumblebees.

The white shoes problem, usually known as the raven’s paradox, is a problem that arises from a fact in logic. It is a logical truism that if a hypothesis implies some observation, then the negation of that observation implies the negation of the hypothesis. So in the case of ravens, the HD model of confirmation, if x is a raven then x is black, is logically equivalent to if x is not black then x is not a raven. But as before we saw that if we find something that is black and a raven, then it confirms the first implication, so a white shoe that is neither black nor a raven will confirm the second implication. So white shoes confirm that all ravens are black. This is a problem, white shoes shouldn’t confirm anything along those lines.

Second is the irrelevant conjunction problem. Again, it follows from logic. You’ll have to take my word for it, but it is a logical fact that if A implies B, then (A and C) implies B. So we can take some hypothesis about bumblebees dancing to direct others toward honey and attach it to general relativity. General relativity implies that starlight will bend, and logically so will General relativity and bumblebees dancing imply that starlight will bend. The meat of this problem is that if we observe starlight bending, then we confirm both the hypothesis of General relativity, and bumblebees dancing. Hence the name, the problem of irrelevant conjunctions. We could even take this a step further and append bumble bees to the ravens implication such that white shoes confirm that all ravens are black and that bumblebees dance to show where the honey is.

Why is this interesting? Because HD is rather much like a common sense approach to science. If an observation is derived from a hypothesis, then either it is confirmed or disconfirmed by the observation. But common sense is wrong on this point. And that’s what philosophy likes to do. It likes to start from a common sense beginning, and then take it further and see how it fares. Often, it does not do so well. which is why philosophy is interesting, it questions what we take for granted as true and often finds that it doesn’t work. That doesn’t mean it has all the answers, believe me, you don’t go into philosophy for answers, but in some sense, like science, at least we know what doesn’t work.

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For those familiar with bayesianism, the problem of irrelevant conjunctions plagues it as well. First is just that since an irrelevant hypothesis will not impact the probability of an observation, it too will be confirmed by observation. Or, in a more technical perspective, the HD model is a subset of bayesianism, HD is just when the likelihood of Pr(observation|hypothesis & irrelevant hypothesis)=1, which then means that the probability of Pr(hypothesis & irrelevant hypothesis | observation) = Pr(hypothesis & irrelevant hypothesis) / Pr (observation) under Bayes’ theorem. And this is always greater than than Pr(hypothesis & irrelevant hypothesis) because Pr(observation) < 1.