nhaliday + neuro   244

Lateralization of brain function - Wikipedia
Language functions such as grammar, vocabulary and literal meaning are typically lateralized to the left hemisphere, especially in right handed individuals.[3] While language production is left-lateralized in up to 90% of right-handers, it is more bilateral, or even right-lateralized, in approximately 50% of left-handers.[4]

Broca's area and Wernicke's area, two areas associated with the production of speech, are located in the left cerebral hemisphere for about 95% of right-handers, but about 70% of left-handers.[5]:69

Auditory and visual processing
The processing of visual and auditory stimuli, spatial manipulation, facial perception, and artistic ability are represented bilaterally.[4] Numerical estimation, comparison and online calculation depend on bilateral parietal regions[6][7] while exact calculation and fact retrieval are associated with left parietal regions, perhaps due to their ties to linguistic processing.[6][7]


Depression is linked with a hyperactive right hemisphere, with evidence of selective involvement in "processing negative emotions, pessimistic thoughts and unconstructive thinking styles", as well as vigilance, arousal and self-reflection, and a relatively hypoactive left hemisphere, "specifically involved in processing pleasurable experiences" and "relatively more involved in decision-making processes".

Chaos and Order; the right and left hemispheres: https://orthosphere.wordpress.com/2018/05/23/chaos-and-order-the-right-and-left-hemispheres/
In The Master and His Emissary, Iain McGilchrist writes that a creature like a bird needs two types of consciousness simultaneously. It needs to be able to focus on something specific, such as pecking at food, while it also needs to keep an eye out for predators which requires a more general awareness of environment.

These are quite different activities. The Left Hemisphere (LH) is adapted for a narrow focus. The Right Hemisphere (RH) for the broad. The brains of human beings have the same division of function.

The LH governs the right side of the body, the RH, the left side. With birds, the left eye (RH) looks for predators, the right eye (LH) focuses on food and specifics. Since danger can take many forms and is unpredictable, the RH has to be very open-minded.

The LH is for narrow focus, the explicit, the familiar, the literal, tools, mechanism/machines and the man-made. The broad focus of the RH is necessarily more vague and intuitive and handles the anomalous, novel, metaphorical, the living and organic. The LH is high resolution but narrow, the RH low resolution but broad.

The LH exhibits unrealistic optimism and self-belief. The RH has a tendency towards depression and is much more realistic about a person’s own abilities. LH has trouble following narratives because it has a poor sense of “wholes.” In art it favors flatness, abstract and conceptual art, black and white rather than color, simple geometric shapes and multiple perspectives all shoved together, e.g., cubism. Particularly RH paintings emphasize vistas with great depth of field and thus space and time,[1] emotion, figurative painting and scenes related to the life world. In music, LH likes simple, repetitive rhythms. The RH favors melody, harmony and complex rhythms.


Schizophrenia is a disease of extreme LH emphasis. Since empathy is RH and the ability to notice emotional nuance facially, vocally and bodily expressed, schizophrenics tend to be paranoid and are often convinced that the real people they know have been replaced by robotic imposters. This is at least partly because they lose the ability to intuit what other people are thinking and feeling – hence they seem robotic and suspicious.

Oswald Spengler’s The Decline of the West as well as McGilchrist characterize the West as awash in phenomena associated with an extreme LH emphasis. Spengler argues that Western civilization was originally much more RH (to use McGilchrist’s categories) and that all its most significant artistic (in the broadest sense) achievements were triumphs of RH accentuation.

The RH is where novel experiences and the anomalous are processed and where mathematical, and other, problems are solved. The RH is involved with the natural, the unfamiliar, the unique, emotions, the embodied, music, humor, understanding intonation and emotional nuance of speech, the metaphorical, nuance, and social relations. It has very little speech, but the RH is necessary for processing all the nonlinguistic aspects of speaking, including body language. Understanding what someone means by vocal inflection and facial expressions is an intuitive RH process rather than explicit.


RH is very much the center of lived experience; of the life world with all its depth and richness. The RH is “the master” from the title of McGilchrist’s book. The LH ought to be no more than the emissary; the valued servant of the RH. However, in the last few centuries, the LH, which has tyrannical tendencies, has tried to become the master. The LH is where the ego is predominantly located. In split brain patients where the LH and the RH are surgically divided (this is done sometimes in the case of epileptic patients) one hand will sometimes fight with the other. In one man’s case, one hand would reach out to hug his wife while the other pushed her away. One hand reached for one shirt, the other another shirt. Or a patient will be driving a car and one hand will try to turn the steering wheel in the opposite direction. In these cases, the “naughty” hand is usually the left hand (RH), while the patient tends to identify herself with the right hand governed by the LH. The two hemispheres have quite different personalities.

The connection between LH and ego can also be seen in the fact that the LH is competitive, contentious, and agonistic. It wants to win. It is the part of you that hates to lose arguments.

Using the metaphor of Chaos and Order, the RH deals with Chaos – the unknown, the unfamiliar, the implicit, the emotional, the dark, danger, mystery. The LH is connected with Order – the known, the familiar, the rule-driven, the explicit, and light of day. Learning something means to take something unfamiliar and making it familiar. Since the RH deals with the novel, it is the problem-solving part. Once understood, the results are dealt with by the LH. When learning a new piece on the piano, the RH is involved. Once mastered, the result becomes a LH affair. The muscle memory developed by repetition is processed by the LH. If errors are made, the activity returns to the RH to figure out what went wrong; the activity is repeated until the correct muscle memory is developed in which case it becomes part of the familiar LH.

Science is an attempt to find Order. It would not be necessary if people lived in an entirely orderly, explicit, known world. The lived context of science implies Chaos. Theories are reductive and simplifying and help to pick out salient features of a phenomenon. They are always partial truths, though some are more partial than others. The alternative to a certain level of reductionism or partialness would be to simply reproduce the world which of course would be both impossible and unproductive. The test for whether a theory is sufficiently non-partial is whether it is fit for purpose and whether it contributes to human flourishing.


Analytic philosophers pride themselves on trying to do away with vagueness. To do so, they tend to jettison context which cannot be brought into fine focus. However, in order to understand things and discern their meaning, it is necessary to have the big picture, the overview, as well as the details. There is no point in having details if the subject does not know what they are details of. Such philosophers also tend to leave themselves out of the picture even when what they are thinking about has reflexive implications. John Locke, for instance, tried to banish the RH from reality. All phenomena having to do with subjective experience he deemed unreal and once remarked about metaphors, a RH phenomenon, that they are “perfect cheats.” Analytic philosophers tend to check the logic of the words on the page and not to think about what those words might say about them. The trick is for them to recognize that they and their theories, which exist in minds, are part of reality too.

The RH test for whether someone actually believes something can be found by examining his actions. If he finds that he must regard his own actions as free, and, in order to get along with other people, must also attribute free will to them and treat them as free agents, then he effectively believes in free will – no matter his LH theoretical commitments.


We do not know the origin of life. We do not know how or even if consciousness can emerge from matter. We do not know the nature of 96% of the matter of the universe. Clearly all these things exist. They can provide the subject matter of theories but they continue to exist as theorizing ceases or theories change. Not knowing how something is possible is irrelevant to its actual existence. An inability to explain something is ultimately neither here nor there.

If thought begins and ends with the LH, then thinking has no content – content being provided by experience (RH), and skepticism and nihilism ensue. The LH spins its wheels self-referentially, never referring back to experience. Theory assumes such primacy that it will simply outlaw experiences and data inconsistent with it; a profoundly wrong-headed approach.


Gödel’s Theorem proves that not everything true can be proven to be true. This means there is an ineradicable role for faith, hope and intuition in every moderately complex human intellectual endeavor. There is no one set of consistent axioms from which all other truths can be derived.

Alan Turing’s proof of the halting problem proves that there is no effective procedure for finding effective procedures. Without a mechanical decision procedure, (LH), when it comes to … [more]
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september 2018 by nhaliday
Commentary: Predictions and the brain: how musical sounds become rewarding
did i just learn something big?

Prerecorded music has ABSOLUTELY NO
SURVIVAL reward. Zero. It does not help
with procreation (well, unless you're the
one making the music, then you get
endless sex) and it does not help with
individual survival.
As such, one must seriously self test
(n=1) prerecorded music actually holds
you back.
If you're reading this and you try no
music for 2 weeks and fail, hit me up. I
have some mind blowing stuff to show
you in how you can control others with
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june 2018 by nhaliday
Moravec's paradox - Wikipedia
Moravec's paradox is the discovery by artificial intelligence and robotics researchers that, contrary to traditional assumptions, high-level reasoning requires very little computation, but low-level sensorimotor skills require enormous computational resources. The principle was articulated by Hans Moravec, Rodney Brooks, Marvin Minsky and others in the 1980s. As Moravec writes, "it is comparatively easy to make computers exhibit adult level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility".[1]

Similarly, Minsky emphasized that the most difficult human skills to reverse engineer are those that are unconscious. "In general, we're least aware of what our minds do best", he wrote, and added "we're more aware of simple processes that don't work well than of complex ones that work flawlessly".[2]


One possible explanation of the paradox, offered by Moravec, is based on evolution. All human skills are implemented biologically, using machinery designed by the process of natural selection. In the course of their evolution, natural selection has tended to preserve design improvements and optimizations. The older a skill is, the more time natural selection has had to improve the design. Abstract thought developed only very recently, and consequently, we should not expect its implementation to be particularly efficient.

As Moravec writes:

Encoded in the large, highly evolved sensory and motor portions of the human brain is a billion years of experience about the nature of the world and how to survive in it. The deliberate process we call reasoning is, I believe, the thinnest veneer of human thought, effective only because it is supported by this much older and much more powerful, though usually unconscious, sensorimotor knowledge. We are all prodigious olympians in perceptual and motor areas, so good that we make the difficult look easy. Abstract thought, though, is a new trick, perhaps less than 100 thousand years old. We have not yet mastered it. It is not all that intrinsically difficult; it just seems so when we do it.[3]

A compact way to express this argument would be:

- We should expect the difficulty of reverse-engineering any human skill to be roughly proportional to the amount of time that skill has been evolving in animals.
- The oldest human skills are largely unconscious and so appear to us to be effortless.
- Therefore, we should expect skills that appear effortless to be difficult to reverse-engineer, but skills that require effort may not necessarily be difficult to engineer at all.
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june 2018 by nhaliday
What's Wrong With Growing Blobs of Brain Tissue? - The Atlantic
These increasingly complex organoids aren't conscious—but we might not know when they cross that line.

I don't know why you would even *want* to do this tbh... What's the application?
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april 2018 by nhaliday
Eliminative materialism - Wikipedia
Eliminative materialism (also called eliminativism) is the claim that people's common-sense understanding of the mind (or folk psychology) is false and that certain classes of mental states that most people believe in do not exist.[1] It is a materialist position in the philosophy of mind. Some supporters of eliminativism argue that no coherent neural basis will be found for many everyday psychological concepts such as belief or desire, since they are poorly defined. Rather, they argue that psychological concepts of behaviour and experience should be judged by how well they reduce to the biological level.[2] Other versions entail the non-existence of conscious mental states such as pain and visual perceptions.[3]

Eliminativism about a class of entities is the view that that class of entities does not exist.[4] For example, materialism tends to be eliminativist about the soul; modern chemists are eliminativist about phlogiston; and modern physicists are eliminativist about the existence of luminiferous aether. Eliminative materialism is the relatively new (1960s–1970s) idea that certain classes of mental entities that common sense takes for granted, such as beliefs, desires, and the subjective sensation of pain, do not exist.[5][6] The most common versions are eliminativism about propositional attitudes, as expressed by Paul and Patricia Churchland,[7] and eliminativism about qualia (subjective interpretations about particular instances of subjective experience), as expressed by Daniel Dennett and Georges Rey.[3] These philosophers often appeal to an introspection illusion.

In the context of materialist understandings of psychology, eliminativism stands in opposition to reductive materialism which argues that mental states as conventionally understood do exist, and that they directly correspond to the physical state of the nervous system.[8][need quotation to verify] An intermediate position is revisionary materialism, which will often argue that the mental state in question will prove to be somewhat reducible to physical phenomena—with some changes needed to the common sense concept.

Since eliminative materialism claims that future research will fail to find a neuronal basis for various mental phenomena, it must necessarily wait for science to progress further. One might question the position on these grounds, but other philosophers like Churchland argue that eliminativism is often necessary in order to open the minds of thinkers to new evidence and better explanations.[8]
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april 2018 by nhaliday
Theory of Self-Reproducing Automata - John von Neumann

Comparisons between computing machines and the nervous systems. Estimates of size for computing machines, present and near future.

Estimates for size for the human central nervous system. Excursus about the “mixed” character of living organisms. Analog and digital elements. Observations about the “mixed” character of all componentry, artificial as well as natural. Interpretation of the position to be taken with respect to these.

Evaluation of the discrepancy in size between artificial and natural automata. Interpretation of this discrepancy in terms of physical factors. Nature of the materials used.

The probability of the presence of other intellectual factors. The role of complication and the theoretical penetration that it requires.

Questions of reliability and errors reconsidered. Probability of individual errors and length of procedure. Typical lengths of procedure for computing machines and for living organisms--that is, for artificial and for natural automata. Upper limits on acceptable probability of error in individual operations. Compensation by checking and self-correcting features.

Differences of principle in the way in which errors are dealt with in artificial and in natural automata. The “single error” principle in artificial automata. Crudeness of our approach in this case, due to the lack of adequate theory. More sophisticated treatment of this problem in natural automata: The role of the autonomy of parts. Connections between this autonomy and evolution.

- 10^10 neurons in brain, 10^4 vacuum tubes in largest computer at time
- machines faster: 5 ms from neuron potential to neuron potential, 10^-3 ms for vacuum tubes

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april 2018 by nhaliday
Complexity no Bar to AI - Gwern.net
Critics of AI risk suggest diminishing returns to computing (formalized asymptotically) means AI will be weak; this argument relies on a large number of questionable premises and ignoring additional resources, constant factors, and nonlinear returns to small intelligence advantages, and is highly unlikely. (computer science, transhumanism, AI, R)
created: 1 June 2014; modified: 01 Feb 2018; status: finished; confidence: likely; importance: 10
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april 2018 by nhaliday
Is the human brain analog or digital? - Quora
The brain is neither analog nor digital, but works using a signal processing paradigm that has some properties in common with both.
Unlike a digital computer, the brain does not use binary logic or binary addressable memory, and it does not perform binary arithmetic. Information in the brain is represented in terms of statistical approximations and estimations rather than exact values. The brain is also non-deterministic and cannot replay instruction sequences with error-free precision. So in all these ways, the brain is definitely not "digital".
At the same time, the signals sent around the brain are "either-or" states that are similar to binary. A neuron fires or it does not. These all-or-nothing pulses are the basic language of the brain. So in this sense, the brain is computing using something like binary signals. Instead of 1s and 0s, or "on" and "off", the brain uses "spike" or "no spike" (referring to the firing of a neuron).
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april 2018 by nhaliday
Society of Mind - Wikipedia
A core tenet of Minsky's philosophy is that "minds are what brains do". The society of mind theory views the human mind and any other naturally evolved cognitive systems as a vast society of individually simple processes known as agents. These processes are the fundamental thinking entities from which minds are built, and together produce the many abilities we attribute to minds. The great power in viewing a mind as a society of agents, as opposed to the consequence of some basic principle or some simple formal system, is that different agents can be based on different types of processes with different purposes, ways of representing knowledge, and methods for producing results.

This idea is perhaps best summarized by the following quote:

What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle. —Marvin Minsky, The Society of Mind, p. 308


The modular organization of human anatomical
brain networks: Accounting for the cost of wiring: https://www.mitpressjournals.org/doi/pdfplus/10.1162/NETN_a_00002
Brain networks are expected to be modular. However, existing techniques for estimating a network’s modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.
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april 2018 by nhaliday
The Hanson-Yudkowsky AI-Foom Debate - Machine Intelligence Research Institute
How Deviant Recent AI Progress Lumpiness?: http://www.overcomingbias.com/2018/03/how-deviant-recent-ai-progress-lumpiness.html
I seem to disagree with most people working on artificial intelligence (AI) risk. While with them I expect rapid change once AI is powerful enough to replace most all human workers, I expect this change to be spread across the world, not concentrated in one main localized AI system. The efforts of AI risk folks to design AI systems whose values won’t drift might stop global AI value drift if there is just one main AI system. But doing so in a world of many AI systems at similar abilities levels requires strong global governance of AI systems, which is a tall order anytime soon. Their continued focus on preventing single system drift suggests that they expect a single main AI system.

The main reason that I understand to expect relatively local AI progress is if AI progress is unusually lumpy, i.e., arriving in unusually fewer larger packages rather than in the usual many smaller packages. If one AI team finds a big lump, it might jump way ahead of the other teams.

However, we have a vast literature on the lumpiness of research and innovation more generally, which clearly says that usually most of the value in innovation is found in many small innovations. We have also so far seen this in computer science (CS) and AI. Even if there have been historical examples where much value was found in particular big innovations, such as nuclear weapons or the origin of humans.

Apparently many people associated with AI risk, including the star machine learning (ML) researchers that they often idolize, find it intuitively plausible that AI and ML progress is exceptionally lumpy. Such researchers often say, “My project is ‘huge’, and will soon do it all!” A decade ago my ex-co-blogger Eliezer Yudkowsky and I argued here on this blog about our differing estimates of AI progress lumpiness. He recently offered Alpha Go Zero as evidence of AI lumpiness:


In this post, let me give another example (beyond two big lumps in a row) of what could change my mind. I offer a clear observable indicator, for which data should have available now: deviant citation lumpiness in recent ML research. One standard measure of research impact is citations; bigger lumpier developments gain more citations that smaller ones. And it turns out that the lumpiness of citations is remarkably constant across research fields! See this March 3 paper in Science:

I Still Don’t Get Foom: http://www.overcomingbias.com/2014/07/30855.html
All of which makes it look like I’m the one with the problem; everyone else gets it. Even so, I’m gonna try to explain my problem again, in the hope that someone can explain where I’m going wrong. Here goes.

“Intelligence” just means an ability to do mental/calculation tasks, averaged over many tasks. I’ve always found it plausible that machines will continue to do more kinds of mental tasks better, and eventually be better at pretty much all of them. But what I’ve found it hard to accept is a “local explosion.” This is where a single machine, built by a single project using only a tiny fraction of world resources, goes in a short time (e.g., weeks) from being so weak that it is usually beat by a single human with the usual tools, to so powerful that it easily takes over the entire world. Yes, smarter machines may greatly increase overall economic growth rates, and yes such growth may be uneven. But this degree of unevenness seems implausibly extreme. Let me explain.

If we count by economic value, humans now do most of the mental tasks worth doing. Evolution has given us a brain chock-full of useful well-honed modules. And the fact that most mental tasks require the use of many modules is enough to explain why some of us are smarter than others. (There’d be a common “g” factor in task performance even with independent module variation.) Our modules aren’t that different from those of other primates, but because ours are different enough to allow lots of cultural transmission of innovation, we’ve out-competed other primates handily.

We’ve had computers for over seventy years, and have slowly build up libraries of software modules for them. Like brains, computers do mental tasks by combining modules. An important mental task is software innovation: improving these modules, adding new ones, and finding new ways to combine them. Ideas for new modules are sometimes inspired by the modules we see in our brains. When an innovation team finds an improvement, they usually sell access to it, which gives them resources for new projects, and lets others take advantage of their innovation.


In Bostrom’s graph above the line for an initially small project and system has a much higher slope, which means that it becomes in a short time vastly better at software innovation. Better than the entire rest of the world put together. And my key question is: how could it plausibly do that? Since the rest of the world is already trying the best it can to usefully innovate, and to abstract to promote such innovation, what exactly gives one small project such a huge advantage to let it innovate so much faster?


In fact, most software innovation seems to be driven by hardware advances, instead of innovator creativity. Apparently, good ideas are available but must usually wait until hardware is cheap enough to support them.

Yes, sometimes architectural choices have wider impacts. But I was an artificial intelligence researcher for nine years, ending twenty years ago, and I never saw an architecture choice make a huge difference, relative to other reasonable architecture choices. For most big systems, overall architecture matters a lot less than getting lots of detail right. Researchers have long wandered the space of architectures, mostly rediscovering variations on what others found before.

Some hope that a small project could be much better at innovation because it specializes in that topic, and much better understands new theoretical insights into the basic nature of innovation or intelligence. But I don’t think those are actually topics where one can usefully specialize much, or where we’ll find much useful new theory. To be much better at learning, the project would instead have to be much better at hundreds of specific kinds of learning. Which is very hard to do in a small project.

What does Bostrom say? Alas, not much. He distinguishes several advantages of digital over human minds, but all software shares those advantages. Bostrom also distinguishes five paths: better software, brain emulation (i.e., ems), biological enhancement of humans, brain-computer interfaces, and better human organizations. He doesn’t think interfaces would work, and sees organizations and better biology as only playing supporting roles.


Similarly, while you might imagine someday standing in awe in front of a super intelligence that embodies all the power of a new age, superintelligence just isn’t the sort of thing that one project could invent. As “intelligence” is just the name we give to being better at many mental tasks by using many good mental modules, there’s no one place to improve it. So I can’t see a plausible way one project could increase its intelligence vastly faster than could the rest of the world.

Takeoff speeds: https://sideways-view.com/2018/02/24/takeoff-speeds/
Futurists have argued for years about whether the development of AGI will look more like a breakthrough within a small group (“fast takeoff”), or a continuous acceleration distributed across the broader economy or a large firm (“slow takeoff”).

I currently think a slow takeoff is significantly more likely. This post explains some of my reasoning and why I think it matters. Mostly the post lists arguments I often hear for a fast takeoff and explains why I don’t find them compelling.

(Note: this is not a post about whether an intelligence explosion will occur. That seems very likely to me. Quantitatively I expect it to go along these lines. So e.g. while I disagree with many of the claims and assumptions in Intelligence Explosion Microeconomics, I don’t disagree with the central thesis or with most of the arguments.)
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april 2018 by nhaliday
Fish on Friday | West Hunter
There are parts of Europe, Switzerland and Bavaria for example, that are seriously iodine deficient. This used to be a problem. I wonder if fish on Friday ameliorated it: A three-ounce serving size of cod provides your body with 99 micrograms of iodine, or 66% of the recommended amount per day.

Thinking further, it wasn’t just Fridays: there were ~130 days a years when the Catholic Church banned flesh.

Gwern on modern iodine-deficiency: https://westhunt.wordpress.com/2017/10/28/fish-on-friday/#comment-97137
population surveys indicate lots of people are iodine-insufficient even in the US or UK where the problem should’ve been permanently solved a century ago
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october 2017 by nhaliday
New Theory Cracks Open the Black Box of Deep Learning | Quanta Magazine
A new idea called the “information bottleneck” is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.

sounds like he's just talking about autoencoders?
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september 2017 by nhaliday
Of Mice and Men | West Hunter
It’s not always easy figuring out how a pathogen causes disease. There is an example in mice for which the solution was very difficult, so difficult that we would probably have failed to discover the cause of a similarly obscure infectious disease in humans.

Mycoplasma pulmonis causes a chronic obstructive lung disease in mice, but it wasn’t easy to show this. The disease was first described in 1915, and by 1940, people began to suspect Mycoplasma pulmonis might be the cause. But then again, maybe not. It was often found in mice that seemed healthy. Pure cultures of this organism did not consistently produce lung disease – which means that it didn’t satisfy Koch’s postulates, in particular postulate 1 (The microorganism must be found in abundance in all organisms suffering from the disease, but should not be found in healthy organisms.) and postulate 3 (The cultured microorganism should cause disease when introduced into a healthy organism.).

Well, those postulates are not logic itself, but rather a useful heuristic. Koch knew that, even if lots of other people don’t.

This respiratory disease of mice is long-lasting, but slow to begin. It can take half a lifetime – a mouse lifetime, that is – and that made finding the cause harder. It required patience, which means I certainly couldn’t have done it.

Here’s how they solved it. You can raise germ-free mice. In the early 1970s, researchers injected various candidate pathogens into different groups of germ-free mice and waited to see which, if any, developed this chronic lung disease. It was Mycoplasma pulmonis , all right, but it had taken 60 years to find out.

It turned out that susceptibility differed between different mouse strains – genetic susceptibility was important. Co-infection with other pathogens affected the course of the disease. Microenvironmental details mattered – mainly ammonia in cages where the bedding wasn’t changed often enough. But it didn’t happen without that mycoplasma, which was a key causal link, something every engineer understands but many MDs don’t.

If there was a similarly obscure infectious disease of humans, say one that involved a fairly common bug found in both the just and the unjust, one that took decades for symptoms to manifest – would we have solved it? Probably not.

Cooties are everywhere.

gay germ search: https://westhunt.wordpress.com/2013/07/21/of-mice-and-men/#comment-15905
It’s hard to say, depends on how complicated the path of causation is. Assuming that I’m even right, of course. Some good autopsy studies might be fruitful – you’d look for microanatomical brain differences, as with nartcolepsy. Differences in gene expression, maybe. You could look for a pathogen – using the digital version of RDA (representational difference analysis), say on discordant twins. Do some old-fashioned epidemiology. Look for marker antibodies, signs of some sort of immunological event.

Do all of the above on gay rams – lots easier to get started, much less whining from those being vivisected.

Patrick Moore found the virus causing Kaposi’s sarcoma without any funding at all. I’m sure Peter Thiel could afford a serious try.
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september 2017 by nhaliday
The Genetics of Alzheimer Disease
Twin and family studies indicate that genetic factors are estimated to play a role in at least 80% of AD cases. The inheritance of AD exhibits a dichotomous pattern. On one hand, rare mutations in APP, PSEN1, and PSEN2 virtually guarantee early-onset (<60 years) familial AD, which represents ∼5% of AD. On the other hand, common gene polymorphisms, such as the ε4 and ε2 variants of the APOE gene, can influence susceptibility for ∼50% of the common late-onset AD. These four genes account for 30%–50% of the inheritability of AD. Genome-wide association studies have recently led to the identification of 11 additional AD candidate genes.

Role of Genes and Environments for Explaining Alzheimer Disease: http://jamanetwork.com/journals/jamapsychiatry/fullarticle/209307
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september 2017 by nhaliday
Mechanisms of microbial traversal of the blood–brain barrier
A journey into the brain: insight into how bacterial pathogens cross blood–brain barriers: http://sci-hub.tw/10.1038/nrmicro.2016.178
How do extracellular pathogens cross the blood-brain barrier?: https://www.ncbi.nlm.nih.gov/pubmed/11973156
Defense at the border: the blood–brain barrier versus bacterial foreigners: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3589978/
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september 2017 by nhaliday
Scanners Live in Vain | West Hunter
Of course, finding that the pattern already exists at the age of one month seriously weakens any idea that being poor shrinks the brain: most of the environmental effects you would consider haven’t even come into play in the first four weeks, when babies drink milk, sleep, and poop. Genetics affecting both parents and their children would make more sense, if the pattern shows up so early (and I’ll bet money that, if real,  it shows up well before one month);  but Martha Farah, and the reporter from Nature, Sara Reardon, ARE TOO FUCKING DUMB to realize this.

Correlation between brain volume and IQ is about 0.4 . Shows up clearly in studies with sufficient power.

“poverty affects prenatal environment a lot.” No it does not. “poverty” in this country means having plenty to eat.

The Great IQ Depression: https://westhunt.wordpress.com/2014/03/07/the-great-iq-depression/
We hear that poverty can sap brainpower, reduce frontal lobe function, induce the fantods, etc. But exactly what do we mean by ‘poverty’? If we’re talking about an absolute, rather than relative, standard of living, most of the world today must be in poverty, as well as almost everyone who lived much before the present. Most Chinese are poorer than the official US poverty level, right? The US had fairly rapid economic growth until the last generation or so, so if you go very far back in time, almost everyone was poor, by modern standards. Even those who were considered rich at the time suffered from zero prenatal care, largely useless medicine, tabletless high schools, and slow Internet connections. They had to ride horses that had lousy acceleration and pooped all over the place.

In particular, if all this poverty-gives-you-emerods stuff is true, scholastic achievement should have collapsed in the Great Depression – and with the miracle of epigenetics, most of us should still be suffering those bad effects.

But somehow none of this seems to have gone through the formality of actually happening.
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august 2017 by nhaliday
Genes, Evolution and Intelligence
I argue that the g factor meets the fundamental criteria of a scientific construct more fully than any other conception of intelligence. I briefly discuss the evidence regarding the relationship of brain size to intelligence. A review of a large body of evidence demonstrates that there is a g factor in a wide range of species and that, in the species studied, it relates to brain size and is heritable. These findings suggest that many species have evolved a general-purpose mechanism (a general biological intelligence) for dealing with the environments in which they evolved. In spite of numerous studies with considerable statistical power, we know of very few genes that influence g and the effects are very small. Nevertheless, g appears to be highly polygenic. Given the complexity of the human brain, it is not surprising that that one of its primary faculties—intelligence—is best explained by the near infinitesimal model of quantitative genetics.
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august 2017 by nhaliday
Alzheimers | West Hunter
Some disease syndromes almost have to be caused by pathogens – for example, any with a fitness impact (prevalence x fitness reduction) > 2% or so, too big to be caused by mutational pressure. I don’t think that this is the case for AD: it hits so late in life that the fitness impact is minimal. However, that hardly means that it can’t be caused by a pathogen or pathogens – a big fraction of all disease syndromes are, including many that strike in old age. That possibility is always worth checking out, not least because infectious diseases are generally easier to prevent and/or treat.

There is new work that strongly suggests that pathogens are the root cause. It appears that the amyloid is an antimicrobial peptide. amyloid-beta binds to invading microbes and then surrounds and entraps them. ‘When researchers injected Salmonella into mice’s hippocampi, a brain area damaged in Alzheimer’s, A-beta quickly sprang into action. It swarmed the bugs and formed aggregates called fibrils and plaques. “Overnight you see the plaques throughout the hippocampus where the bugs were, and then in each single plaque is a single bacterium,” Tanzi says. ‘

obesity and pathogens: https://westhunt.wordpress.com/2016/05/29/alzheimers/#comment-79757
not sure about this guy, but interesting: https://westhunt.wordpress.com/2016/05/29/alzheimers/#comment-79748

All too often we see large, long-lasting research efforts that never produce, never achieve their goal.

For example, the amyloid hypothesis [accumulation of amyloid-beta oligomers is the cause of Alzheimers] has been dominant for more than 20 years, and has driven development of something like 15 drugs. None of them have worked. At the same time the well-known increased risk from APOe4 has been almost entirely ignored, even though it ought to be a clue to the cause.

In general, when a research effort has been spinning its wheels for a generation or more, shouldn’t we try something different? We could at least try putting a fraction of those research dollars into alternative approaches that have not yet failed repeatedly.

Mostly this applies to research efforts that at least wish they were science. ‘educational research’ is in a special class, and I hardly know what to recommend. Most of the remedial actions that occur to me violate one or more of the Geneva conventions.

APOe4 related to lymphatic system: https://en.wikipedia.org/wiki/Apolipoprotein_E

Look,if I could find out the sort of places that I usually misplace my keys – if I did, which I don’t – I could find the keys more easily the next time I lose them. If you find out that practitioners of a given field are not very competent, it marks that field as a likely place to look for relatively easy discovery. Thus medicine is a promising field, because on the whole doctors are not terribly good investigators. For example, none of the drugs developed for Alzheimers have worked at all, which suggests that our ideas on the causation of Alzheimers are likely wrong. Which suggests that it may (repeat may) be possible to make good progress on Alzheimers, either by an entirely empirical approach, which is way underrated nowadays, or by dumping the current explanation, finding a better one, and applying it.

You could start by looking at basic notions of field X and asking yourself: How do we really know that? Is there serious statistical evidence? Does that notion even accord with basic theory? This sort of checking is entirely possible. In most of the social sciences, we don’t, there isn’t, and it doesn’t.

Hygiene and the world distribution of Alzheimer’s disease: Epidemiological evidence for a relationship between microbial environment and age-adjusted disease burden: https://academic.oup.com/emph/article/2013/1/173/1861845/Hygiene-and-the-world-distribution-of-Alzheimer-s

Amyloid-β peptide protects against microbial infection in mouse and worm models of Alzheimer’s disease: http://stm.sciencemag.org/content/8/340/340ra72

Fungus, the bogeyman: http://www.economist.com/news/science-and-technology/21676754-curious-result-hints-possibility-dementia-caused-fungal
Fungus and dementia
paper: http://www.nature.com/articles/srep15015
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july 2017 by nhaliday
A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence | bioRxiv
We apply MTAG to three large GWAS: Sniekers et al (2017) on intelligence, Okbay et al. (2016) on Educational attainment, and Hill et al. (2016) on household income. By combining these three samples our functional sample size increased from 78 308 participants to 147 194. We found 107 independent loci associated with intelligence, implicating 233 genes, using both SNP-based and gene-based GWAS. We find evidence that neurogenesis may explain some of the biological differences in intelligence as well as genes expressed in the synapse and those involved in the regulation of the nervous system.


Finally, using an independent sample of 6 844 individuals we were able to predict 7% of intelligence using SNP data alone.
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july 2017 by nhaliday
Reversal of Fortune | West Hunter
“particularly in the fetus”. You’d think so, but people have looked at Dutch draftees who were in the womb during the famine of 1944. They found no effects of famine exposure on Ravens scores at age 19. Schizophrenia doubled, though. Schiz also doubled in the Chinese cohort exposed to the Great Leap Forward famine.

Cohort Profile: The Dutch Hunger Winter Families Study: https://academic.oup.com/ije/article/36/6/1196/814573
Nutrition and Mental Performance: https://sci-hub.bz/10.1126/science.178.4062.708
Schizophrenia after prenatal exposure to the Dutch Hunger Winter of 1944-1945: https://sci-hub.bz/10.1001/archpsyc.1992.01820120071010
Prenatal famine exposure and cognition at age 59 years: https://sci-hub.bz/10.1093/ije/dyq261

You might be right. There is reason to suspect that prenatal exposure to alcohol is far riskier in some populations than others – in particular populations that have limited historical exposure to alcohol. Fetal Alcohol Syndrome (FAS) is very rare in France, for example – yet they drink, I’m told.

The kind of conservatism that shows up politically doesn’t have any predictive value. In other words, liars and morons. They’re why God made baseball bats. Once upon a time, I said this: “The American right doesn’t have room for anyone who knows jack shit about anything, or whose predictions have ever come true.” I’ll stick with that.

full quote here: http://www.rpgcodex.net/forums/index.php?threads/planescape-torment-problems.9208/
The American right doesn't have room for anyone who knows jack shit about anything, or whose predictions have ever come true. Of course they're all liars. In the words of one of their semi-prominent members, himself plenty despicable: "Science, logic, rational inquiry, thoughtful reflection, mean nothing to them. It's all posturing and moral status games and sucking up to halfwits like GWB and clinging to crackpot religion, and of course amoral careerism. " I think my correspondent forgot to mention their propensity for eating shit and rolling around in their own vomit, but nobody's perfect.

I’ve mused that it’s generally believed that iodine benefits females more than males, and the timing of iodization in the US matches up reasonably well with the rise of feminism…
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may 2017 by nhaliday
Links 5/17: Rip Van Linkle | Slate Star Codex
More on Low-Trust Russia: Do Russian Who Wants To Be A Millionaire contestants avoid asking the audience because they expect audience members to deliberately mislead them?

Xenocrypt on the math of economic geography: “A party’s voters should get more or less seats based on the shape of the monotonic curve with integral one they can be arranged in” might sound like a very silly belief, but it is equivalent to the common mantra that you deserve to lose if your voters are ‘too clustered’”

Okay, look, I went way too long between writing up links posts this time, so you’re getting completely dated obsolete stuff like Actually, Neil Gorsuch Is A Champion Of The Little Guy. But aside from the Gorsuch reference this is actually pretty timeless – basically an argument for strict constructionism on the grounds that “a flexible, living, bendable law will always tend to be bent in the direction of the powerful.”

Otium: Are Adult Developmental Stages Real? Looks at Kohlberg, Kegan, etc.

I mentioned the debate over 5-HTTLPR, a gene supposedly linked to various mental health outcomes, in my review of pharmacogenomics. Now a very complete meta-analysis finds that a lot of the hype around it isn’t true. This is pretty impressive since there are dozens of papers claiming otherwise, and maybe the most striking example yet of how apparently well-replicated a finding can be and still fail to pan out.

Rootclaim describes itself as a crowd-sourced argument mapper. See for example its page on who launched the chemical attack in Syria.

Apparently if you just kill off all the cells that are growing too old, you can partly reverse organisms’ aging (paper, popular article)

The Politics Of The Gene: “Contrary to expectations, however, we find little evidence that it is more common for whites, the socioeconomically advantaged, or political conservatives to believe that genetics are important for health and social outcomes.”

Siberian Fox linked me to two studies that somewhat contradicted my minimalist interpretation of childhood trauma here: Alemany on psychosis and Turkheimer on harsh punishment.

Lyrebird is an AI project which, if fed samples of a person’s voice, can read off any text you want in the same voice. See their demo with Obama, Trump, and Hillary (I find them instantly recognizable but not at all Turing-passing). They say making this available is ethical because it raises awareness of the potential risk, which a Facebook friend compared to “selling nukes to ISIS in order to raise awareness of the risk of someone selling nukes to ISIS.”

Freddie deBoer gives lots of evidence that there is no shortage of qualified STEM workers relative to other fields and the industry is actually pretty saturated. But Wall Street Journal seems to think they have evidence for the opposite? Curious what all of the tech workers here think.

Scott Sumner: How Can There Be A Shortage Of Construction Workers? That is, is it at all plausible that (as help wanted ads would suggest) there are areas where construction companies can’t find unskilled laborers willing to work for $90,000/year? Sumner splits this question in two – first, an economics question of why an efficient market wouldn’t cause salaries to rise to a level that guarantees all jobs get filled. And second, a political question of how this could happen in a country where we’re constantly told that unskilled men are desperate because there are no job opportunities for them anymore. The answers seem to be “there’s a neat but complicated economics reason for the apparent inefficiency” and “the $90,000 number is really misleading but there may still be okay-paying construction jobs going unfilled and that’s still pretty strange”.

Study which is so delightfully contrarian I choose to reblog it before reading it all the way through: mandatory class attendance policies in college decrease grades by preventing students from making rational decisions about when and how to study.
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may 2017 by nhaliday
Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network
Towards explaining non-shared-environment effects on intelligence, psychiatric disorders, and other cognitive traits - developmental noise such as post-conception mutations in individual cells or groups of cells
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may 2017 by nhaliday
Victorian naturalists | EVOLVING ECONOMICS
Being a naturalist in the Victorian era was a different exercise to today. From Darwin’s The Descent of Man:

Many kinds of monkeys have a strong taste for tea, coffee, and spiritous liquors: they will also, as I have myself seen, smoke tobacco with pleasure. (6. The same tastes are common to some animals much lower in the scale. Mr. A. Nichols informs me that he kept in Queensland, in Australia, three individuals of the Phaseolarctus cinereus [koalas]; and that, without having been taught in any way, they acquired a strong taste for rum, and for smoking tobacco.) Brehm asserts that the natives of north-eastern Africa catch the wild baboons by exposing vessels with strong beer, by which they are made drunk. He has seen some of these animals, which he kept in confinement, in this state; and he gives a laughable account of their behaviour and strange grimaces. On the following morning they were very cross and dismal; they held their aching heads with both hands, and wore a most pitiable expression: when beer or wine was offered them, they turned away with disgust, but relished the juice of lemons. An American monkey, an Ateles, after getting drunk on brandy, would never touch it again, and thus was wiser than many men. These trifling facts prove how similar the nerves of taste must be in monkeys and man, and how similarly their whole nervous system is affected.
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may 2017 by nhaliday
Typos | West Hunter
In a simple model, a given mutant has an equilibrium frequency μ/s, when μ is the mutation rate from good to bad alleles and s is the size of the selective disadvantage. To estimate the total impact of mutation at that locus, you multiply the frequency by the expected harm, s: which means that the fitness decrease (from effects at that locus) is just μ, the mutation rate. If we assume that these fitness effects are multiplicative, the total fitness decrease (also called ‘mutational load’) is approximately 1 – exp(-U), when U is where U=Σ2μ, the total number of new harmful mutations per diploid individual.


interesting, suggestive comment on Africa:
I have reason to believe that few people understand genetic load very well, probably for self-referential reasons, but better explanations are possible.

One key point is that the amount of neutral variation is determined by the long-term mutational rate and population history, while the amount of deleterious variation [genetic load] is set by the selective pressures and the prevailing mutation rate over a much shorter time scale. For example, if you consider the class of mutations that reduce fitness by 1%, what matters is the past few thousand years, not the past few tens or hundreds of of thousands of years.


So, assuming that African populations have more neutral variation than non-African populations (which is well-established), what do we expect to see when we compare the levels of probably-damaging mutations in those two populations? If the Africans and non-Africans had experienced essentially similar mutation rates and selective pressures over the past few thousand years, we would expect to see the same levels of probably-damaging mutations. Bottlenecks that happened at the last glacial maximum or in the expansion out of Africa are irrelevant – too long ago to matter.

But we don’t. The amount of rare synonymous stuff is about 22% higher in Africans. The amount of rare nonsynonymous stuff (usually at least slightly deleterious) is 20.6% higher. The number of rare variants predicted to be more deleterious is ~21.6% higher. The amount of stuff predicted to be even more deleterious is ~27% higher. The number of harmful looking loss-of-function mutations (yet more deleterious) is 25% higher.

It looks as if the excess grows as the severity of the mutations increases. There is a scenario in which this is possible: the mutation rate in Africa has increased recently. Not yesterday, but, say, over the past few thousand years.


What is the most likely cause of such variations in the mutation rate? Right now, I’d say differences in average paternal age. We know that modest differences (~5 years) in average paternal age can easily generate ~20% differences in the mutation rate. Such between-population differences in mutation rates seem quite plausible, particularly since the Neolithic.
more recent: https://westhunt.wordpress.com/2017/06/06/happy-families-are-all-alike-every-unhappy-family-is-unhappy-in-its-own-way/#comment-92491
Probably not, but the question is complex: depends on the shape of the deleterious mutational spectrum [which we don’t know], ancient and recent demography, paternal age, and the extent of truncation selection in the population.
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may 2017 by nhaliday
Allelic Differentiation Of Complex Trait Loci Across Human Populations | bioRxiv
We observed variation in allelic differentiation between populations at tissue-specific expression quantitative trait loci (eQTL), with greatest effects found for genes expressed in a region of the brain that has been linked to schizophrenia and bipolar disorder. Consistent with this, genome-wide association study regions also showed high levels of population differentiation for these diseases suggesting that loci linked to neurological function evolve rapidly. Clear differences for genetic structure in populations were observed for closely related complex human phenotypes. We show that the evolutionary forces acting at pleiotropic loci are often neutral by comparing directional effects of traits under selection. Our results illustrate the value of within species comparisons to understanding complex trait evolution.
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april 2017 by nhaliday
Octopuses Do Something Really Strange to Their Genes - The Atlantic
But to what end? RNA editing is still mysterious, and its purpose unclear. Technically, an animal could use it to change the nature of its proteins without altering the underlying DNA instructions. But in practice, this kind of recoding is extremely rare. Only about 3 percent of human genes are ever edited in this way, and the changes are usually restricted to the parts of RNA that are cut out and discarded. To the extent that it happens, it doesn’t seem to be adaptive.

In cephalopods, it’s a different story. Back in 2015, Rosenthal and Eisenberg discovered that RNA editing has gone wild in the longfin inshore squid—a foot-long animal that’s commonly used in neuroscience research. While a typical mammal edits its RNA at just a few hundred sites, the squid was making some 57,000 such edits. These changes weren’t happening in discarded sections of RNA, but in the ones that actually go towards building proteins—the so-called coding regions. They were ten times more common in the squid’s neurons than in its other tissues, and they disproportionately affected proteins involved in its nervous system.
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april 2017 by nhaliday
Extended spider cognition | SpringerLink
Spiders do not seem to be cognitively limited, displaying a large diversity of learning processes, from habituation to contextual learning, including a sense of numerosity. To tease apart the central from the extended cognition, we apply the mutual manipulability criterion, testing the existence of reciprocal causal links between the putative elements of the system. We conclude that the web threads and configurations are integral parts of the cognitive systems. The extension of cognition to the web helps to explain some puzzling features of spider behaviour and seems to promote evolvability within the group, enhancing innovation through cognitive connectivity to variable habitat features. Graded changes in relative brain size could also be explained by outsourcing information processing to environmental features. More generally, niche-constructed structures emerge as prime candidates for extending animal cognition, generating the selective pressures that help to shape the evolving cognitive system.

study  cocktail  bio  nature  neuro  eden  evolution  intelligence  exocortex  retrofit  deep-materialism  quantitative-qualitative  multi  org:mag  org:sci  popsci  summary  nibble  org:inst 
april 2017 by nhaliday
Epidemiology of autism - Wikipedia
This Is How Much of Autism Is Genetic: http://time.com/4956316/how-much-of-autism-is-genetic/
Indeed, when Sandin tracked autism diagnoses over time among the sibling pairs, he found that genetics likely accounts for around 83% of the disorder. That compares to nearly 90% reported in previous studies of twins only. Using the new model, environmental factors probably contribute around 17% to the risk of developing autism.
sapiens  medicine  genetics  variance-components  science-anxiety  psychiatry  disease  neuro  autism  👽  epidemiology  wiki  reference  biodet  paternal-age  behavioral-gen  public-health  multi  news  org:mag  org:sci  india  asia  data  sib-study  study  summary  org:lite 
march 2017 by nhaliday
Cat Ladies | West Hunter
If toxo naturally can make people like cat piss, it’s already preadapted to become (with suitable genetic engineering) the model system for many kinds of infectious behavior modifiers.
west-hunter  sapiens  parasites-microbiome  disease  toxo-gondii  neuro  psychiatry  nature  discussion  commentary  gwern  medicine  🌞  embodied  scitariat  hmm  biotech  biohacking  retrofit  public-health  model-organism  pro-rata  epidemiology  drugs  pharma 
march 2017 by nhaliday
De novo mutations in regulatory elements cause neurodevelopmental disorders | bioRxiv
De novo mutations in hundreds of different genes collectively cause 25-42% of severe developmental disorders (DD). The cause in the remaining cases is largely unknown. The role of de novo mutations in regulatory elements affecting known DD-associated genes or other genes is essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 DD patients. Here we show that de novo mutations in highly conserved fetal-brain active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant two-fold enrichment of recurrently mutated elements. We estimate that, genome-wide, de novo mutations in fetal-brain active elements are likely to be causal for 1-3% of patients without a diagnostic coding variant and that only a small fraction (<2%) of de novo mutations in these elements are pathogenic. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasise the importance of combining functional and evolutionary evidence to delineate regulatory causes of genetic disorders.
study  preprint  bio  sapiens  biodet  genetics  genomics  genetic-load  mutation  developmental  neuro  psychiatry  QTL  🌞  epidemiology  behavioral-gen 
march 2017 by nhaliday
Summary | EWG's 2017 Shopper's Guide to Pesticides in Produce
Three long-term birth cohort studies in the U.S. suggest that pesticides are harming children’s brains. In these studies, researchers found that women’s exposure to pesticides during pregnancy, measured through urine samples, was associated with negative impacts on their children’s IQ and neurobehavioral development, as well as with ADHD [attention deficit hyperactivity disorder] diagnoses. Also, one of the studies looked at structural brain growth using magnetic resonance imaging and found that the gray matter was thinner in children the higher their mothers’ exposure to organophosphates, which are used widely in pesticides. I think that’s quite scary.
org:health  data  analysis  health  food  hypochondria  embodied-street-fighting  embodied  reference  sanctity-degradation  multi  org:edu  science-anxiety  study  summary  developmental  neuro  psychiatry 
march 2017 by nhaliday
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