Extremism is no Accident

Gun owners and Muslims have something in common.

One of the watershed events leading up to the American Civil War was the caning of Senator Charles Sumner by Senator Preston Brooks of South Carolina, in 1856. Sumner was an outright abolitionist from Massachusetts, and had just given a landmark speech on the fate of Kansas, upon which the future direction of the nation hinged. Sumner let it all hang out, portraying Kansas as a virgin raped by the slave powers which were working to corrupt its institutions and force it to come into the union as a slave state. Hours long and shooting insults in all directions, it was quite extreme for its time. Two days later Brooks attacked Sumner in the Senate chamber with a metal-topped cane and beat Sumner, who was trapped at his desk, about the head to within an inch of his life. Brooks was assisted by a colleague, congressman Henry Edmundson from Virginia, who held off Sumner's supporters with a pistol.

No event illustrated quite so markedly the depths to which the sectional divide had sunk, or the clash of cultures between the industrializing, striving North, and the feudal South. The action was extremist, but clearly arose from the respective tribal affiliations and ideologies at work. Southerners apparently welcomed it as honor vindicated, while to the North, it exemplified the barbarity inherent in the slave system, not only embodied in the abject subjugation of slaves, but in the moral coursening of their masters.

Turning to today's ideological battles and extremist events, the rote responses by the various communities implicated in the Orlando shootings bring up the issue of collective responsibility. Does being Muslim implicate you and your beliefs in such an event? Does being a member of the NRA with its opposition to controlling military-grade weapons? If a group's ideology is exemplified by such an event, what is the degree of individual responsibility and culpability?

One can turn to the German question as another, closer, historical example. Germans today still bear a stigma and responsibility deriving from the disastrous world wars of the last century. That is as it should be. Germany and Germans are not pacifist, but they have taken on an extra measure of responsibility for restitution viz-a-vis Jews and Israel, and for peace in Europe. Their economic policies may be tending in the opposite direction, but on the whole, they have meant well over the post-war decades, forging a close relationship with France and various structures of European cooperation.

People are part of groups for a reason, and bear both the costs and benefits of their groups. Homosexuals may be so stigmatized by their membership (which is, unlike some other groups under discussion, not a voluntary membership) that they deny that membership and stay in the closet. Southerners dedicated to the perpetuation of slavery were rarely extremist, but derived benefits from extremist acts. The brutality at the margins, vs escaped slaves, exhibitions of black pride, and unsympathetic whites, kept the system intact, for the benefit all those who didn't want to get their hands dirty.

Membership in Islam is less directly culpable, given the large size of the group compared to the proportionately small numbers of extremists. For example, polls that show that a majority of Muslims do not support ISIS, yet the remainder amounts to “roughly 50 million people [who] express sympathy”. Which is quite a large pool of people to draw on, and more importantly a significant problem for the community of Islam as a whole, not to mention the rest of us. The scriptures of Islam are a well from which countless fundamentalists have learned to hate, and to see violence as both beneficial and sacred. While some forms of Islam, notably Sufi-ism, have renounced these aspects of their tradition in wholesale fashion, the dominant forms of Islam today have not. The strain coming from Saudi Arabia is particularly filled with negativity- towards women, towards apostates, towards Shia, towards infidels.

Extremists are not opposed to their group. As a rule, they believe that most members are insufficiently dedicated to the group’s overall goals and ideology. Fundamentalism, be it gun nuttery or Islamism, is usually couched in original scriptures, and a dismissal of the wishy-washy-ness of the mass of members who value civility and moderation over principle. The ideology of the group leads directly to the occurrence of extremists, if only in a minority of cases. It is the ideology that is at fault if, taken seriously, it leads what the rest of us characterize as extremism. And historically, extremism in Islam has been highly successful, providing the military motivation and success that makes so many people Muslim today. Moderates benefit from extremism.

In ideological terms, ideologies such as religions tout themselves as truth in both moral and scientific senses. The latter is naturally absurd, while the former is just as wrong, since morality is never a closed book. However, given the truths that the Koran provides, it is only natural to hate infidels, apostates, and love God, his messenger, and the jihad that will convert the world. Only an attitude of skepticism about these truths would prompt someone to take a more moderate stance, such as accepting the legitimacy of non-Muslim narratives and approaches to life. Why would a community want to foster such skepticism? That would be counter-productive. Thus extremists are countenanced as their over-enthusiastic brethren, as maybe a political problem with regard to the outside world, but far from an ideological or theoretical problem. This makes communities unable to successfully reprove their extremists, be they anti-abortion zealots, islamic terrorists, or gun-rightists.

This is why we need to pay attention to the tenor of the entire community from which extremists spring. It is not Islamophobia to see a fundamental ideological problem within Islam which fosters bigotry, regressive institutions, and violence so pervasively in the Middle East. Turning back to our Civil War, the extremist violence that occurred in the Senate in 1856 was not an isolated incident, but part of a pattern of discontent and insurrection that had been building in the South, especially South Carolina, for decades. Slavery was at the core of a culture that had diverged to a startling degree from that in the North, and elsewhere in the Western world- a relic of feudalism or worse. Its desperation to persist in a fundamentally immoral institution, and spread it to other sections of the frontier, was inimical to modernity and to decency. The ideologies of the North and the South were incompatible, and the sparks of extremist acts such as the caning of Sumner, and the raid on Harper’s Ferry, were harbingers of the cataclysm to come, as well as cultural and ideological divides we still struggle with today.

Postscript: As for gun ideology, it is not as directly militant as fundamentalist Islam. In fact, it entertains a sort of apple pie fantasy, where all gun owners are rock-ribbed patriots standing with their exquisite training and dedication to the CONSTITUTION athwart the forces of chaos and tyranny. The problem here is not (mostly) what the ideology includes, but what it leaves out- which is reality.  Every empirical study shows that the more guns there are, the more deaths, for a variety of causes like suicide, domestic violence, and accidents, not to mention mass murders, where in every recent case the guns were recently purchased for the purpose. Guns are extremely dangerous, and not everyone who has them makes a fetish of personal firearms training and lock-down security.  Clutching their pearls when some extremist uses a legally purchased semi-automatic to mow down innocent people is a clearly insufficient response to the problem by the gun community. A fantasy of responsibility can not hide a reality of frequent irresponsibility and utterly unnecessary danger.

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Perception is Not a One-Way Street

Perceptions happen in the brain as a reality-modeling process that uses input from external senses, but does so gradually in a looping (i.e. Bayesian) refinement process using motor activity to drive attention and sensory perturbation.

The fact that perceptions come via our sensory organs, and stop once those organs are impaired, strongly suggests a simple camera-type model of one-way perceptual flow. Yet, recent research all points in the other direction, that perception is a more active process wherein the sense organs are central, but are also directed by attention and by pre-existing models of the available perceptual field in a top-down way. Thus we end up with a cognitive loop where the mind holds models of reality which are incrementally updated by the senses, but not wiped and replaced as if they were simple video feeds. The model is the perception and is more valuable than the input.

One small example of a top-down element in this cognitive loop is visual attention. Our eyes are little outposts of the brain, and are told where to point. Even if something surprising happens in the visual field, the brain has to do a little processing before shifting attention, and thus the eyeballs, to that event. Our eyes are shifting all the time, being pointed to areas of interest, following movie scenes, words on a page, etc. None of this is directed by the eyes themselves, (including the jittery saccade system), but by higher levels of cognition.

The paper for this week notes ironically that visual perception studies have worked very hard to eliminate eye and other motion from their studies, to provide consistent mapping of what the experimenters present, to where the perceptions show up in visual fields of the brain. Yet motion and directed attention are fundamental to complex sensation.

Other sensory systems vary substantially in their dependence on motion. Hearing is perhaps least dependent, as one can analyze a scene from a stationary position, though movement of either the sound or the subject, in time and space, are extremely helpful to enrich perception. Touch, through our hairs and skin, is intrinsically dependent on movement and action. Taste and smell are also, though in a subtler way. Any monotonic smell will die pretty rapidly, subjectively, as we get used to it. It is the bloom of fresh tastes with each mouthful or new aromas that create sensation, as implied by the expression "clearing the palate". Aside from the issues of the brain's top-down construction of these perceptions through its choices and modeling, there is also the input of motor components directly, and dynamic time elements, that enrich / enliven perception multi-modally, beyond a simple input stream model.

The many loops from sensory (left) to motor (right) parts of the perceptual network. This figure is focused on whisker perception by mice.

The current paper discusses these issues and makes the point that since our senses have always been embodied and in-motion, they are naturally optimized for dynamic learning. And that the brain circuits mediating between sensation and action are pervasive and very difficult to separate in practice. The authors hypothesize very generally that perception consists of a cognitive quasi-steady state where motor cues are consistent with tactile and other sensory cues (assuming a cognitive model within which this consistence is defined), which is then perturbed by changes in any part of the system, especially sensory organ input, upon which the network seeks a new steady state. They term the core of the network the motor-sensory-motor (MSM) loop, thus empahsizing the motor aspects, and somewhat unfairly de-emphasizing the sensory aspects, which after all are specialized for higher abundance and diversity of data than the motor system. But we can grant that they are an integrated system. They also add that much perception is not conscious, so the fixation of a great deal of research on conscious reports, while understandable, is limiting.

"A crucial aspect of such an attractor is that the dynamics leading to it encompass the entire relevant MSM-loop and thus depend on the function transferring sensor motion into receptors activation; this transfer function describes the perceived object or feature via its physical interactions with sensor motion. Thus, ‘memories’ stored in such perceptual attractors are stored in brain-world interactions, rather than in brain internal representations."

A simple experiment. A camera is set up to watch a video screen, which shows  light and dark half-screens which can move side-to-side. The software creates a sensory-motor loop to pan motors on the camera to enable it to track the visual edge, as shown in E. It is evident that there is not much learning involved, but simply a demonstration of an algorithm's effective integration of motor and sensory elements for pursuit of a simple feature.

Eventually, the researchers present some results, from a mathematical model and robot that they have constructed. The robot has a camera and motors to move around with, plus computer and algorithm. The camera only sends change data, as does the retina, not entire visual scenes, and the visual field is extremely simple- a screen with a dark and light side, which can move right or left. The motorized camera system, using equations approximating a MSM loop, can relatively easily home in on and track the visual right/left divider, and thus demonstrate dynamic perception driven by both motor and sensory elements. The cognitive model was naturally implicit in the computer code that ran the system, which was expecting to track just such a light/dark line. One must say that this was not a particularly difficult or novel task, so the heart of the paper is its introductory material.

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This is Progress?

We are eating ourselves out of house and home.

Werner Herzog made a documentary about Chauvet cave, the respository of spectacular cave art from circa 31,000 years ago. One striking aspect is that virtually all the animals pictured there, and whose remains are found there, are extinct. The aurochs, cave bears, steppe bison, northern rinoceri, cave lions, cave hyenas- all gone. These are animals that had taken hundreds of thousands, if not millions years, to evolve, yet a few tens of thousands of years later, they, along with the mammoths and other denizens of countless prior ice ages, are gone. What happened to them? We killed and ate them.

We then proceeded to raise human populations through agriculture, and carve up the Earth's surface for farming. We have been clearing competitors continuously, from wolves and lions, down to insects. After a false start with overly destructive DDT, agriculture has now settled on neonicotinoids, which, while less persistent in the food chain, have created a silent holocaust of insects, resulting in dead zones throughout agricultural areas, the not-so mysterious collapse of bees, and declines in all kinds of once-common insects.

Similarly, the oceans have been vacuumed of fish, with numerous collapsed and collapsing populations. And topping it all off is climate change and ocean acidification, which is gradually finishing the job of killing off Australia's Geat Barrier Reef, many other reefs around the world, as well as terrestrial species at high latitudes and altitudes.

Have humans made progress? We have, in technical, organizational, and even moral terms. But while we pat ourselves on the back for our space age, smart phones, and hyper-connected intelligence, we also live on an ever-more impoverished planet, due mostly to overpopulation plus the very same develpment we value so much. Institutions and ideologies like the Catholic church who continue to see nothing wrong with infinite population increase in a competitive quest for domination by sheer, miserable numbers are, in this limited and declining world, fundamentally immoral.

The US, after its destruction and displacement of Native Americans, has grown up on an ideology of open frontiers and endless space. But now the political and social ramifications of overpopulation and overdevelopment are beginning to be felt. Trumpism is one reaction- the visceral feeling that we just do not have the room any more, given our unwillingness to develop the requisite infrastructure, and our evident environmental degradation, even in a relatively sparsely populated country, for millions of further immigrants.

Economic inequality is not directly associated with this deep underlying Malthusian trend, since humans can degrade their environment under any economic regime- socialist, capitalist, or Keynesian. But it does provide a metaphor, with us humans lording it over our fellow creatures on the planet. Creatures whom we frequently invoke in our art and spiritual rhetoric and claim to regard with caring stewardship, even humane-ness. But then we keep killing and mistreating them anyhow.

We need to take sustainability seriously, both in terms of human populations and stewardship of the planet generally. E. O. Wilson has advocated for returning half our land to the wild, for the creatures that need it so desperately. This would be a supreme act of generosity and abstention. Though not even enough, in this age of global warming, it is part of the answer towards true sustainability.

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Modeling Gene Regulatory Circuitry

The difficult transition from cartoons to quantitative analysis of gene regulation

As noted a few weeks ago, gene regulation is a complicated field, typically with cartoonish views developed from small amounts of data. Mapping out the basic parameters is one thing, but creating quantitative models of how regulation happens in a dynamic environment is something quite different- something still extremely rare. A recent paper uses yeast genetics to develop a more thorough way to model gene regulation, and to decide among and refine such models.

A cartoon of glutamine (nitrogen) source regulation in yeast cells. Glutamine is a good food, and tif available outside, turns off the various genes needed to synthesize it. Solid lines are known interactions, and dashed lines are marginal or hypothesized interactions. Dal80 and Gzf both form dimers, which act more strongly (as inhibitor and activator, respectively) than single proteins.

When times are good for yeast cells, in nitrogen terms, an upstream signaling system inhibits the gene activators Gat1 and Gln3, leaving the repressors Dal80 and Gzf3 present and active to repress the various target genes that contribute to the synthesis of the key nitrogen-containing molecule glutamine, since it is available as food. All these regulators bind similiar sequences, the GATA motif, near their target genes, (which number about 90), so presence of the repressors can block the activity of the activators as well as shutting off gene expression directly. Conversely, when times are bad and no glutamine is coming in as food, then the suite of glutamine synthesis genes are turned on by Gat1 and Gln3.

Binding site preferences for each regulatory protein discussed. One can tell that they are not always very well-defined.

But things are not so simple, since, evolution being free to come up with any old system and always tinkering with its inheritance, there are feedback loops in several places which exist, at least in part to provide a robust on/off switch out of this analog logic. In fact, the GAT1, DAL80, and GZF genes each have the GATA motif in their own regulatory regions. Even with such a small system, arrows are going every which way, and soon it is very difficult to come up with a defensible, intuitive understanding of how the network behaves.

Edging towards a model. Individual aspects of the known or hypothesized interactions are encoded in computable form.

The data behind the work is a collection of mRNA abundance (i.e. gene expression) studies run under various conditions, especially in mutants of the various genes, and under conditions of nitrogen rich or poor conditions. Panels of the abundance of all mRNAs of interest can be easily run- the problem really is interpretation, and the generation or design of the various mutants and environmental conditions to be informative perturbations.

This is where modelling comes into play. The authors set up the known and hypothesized interactions, each into its own equation, whose parameters could vary. Though the number of elements are few, the large number of interactions / equations meant the models, (with 5 interactions, 13 states, and 41 parameters), given a partial set of data, could not be solved analytically, but were rather approximated by Monte Carlo methods, which is to say, by guessing with sample data. Models with various hypothesized interactions were compared with each other in performance over perturbation, where the model is given a change in conditions, such as a switch to low-nitrogen medium, or an inactivating mutation in one component. The model comparison method was Bayesian because it was iterative and took into account well-known data, such as the established interactions and their key parameter levels, wherever known.

Given a model, its ability to match the experimental data from the mRNA expression profiles under various conditions can be measured, adjusted, and re-iterated. Many models can be compared, and eventually a competitive process reveals which models work better. This is informative if the models are sufficiently detailed, and there is enough detailed data to measure them on, which is one of the strong points of this well-studied regulatory system. Whether this method can be extended to other systems with far less data is questionable.

In this case, one hypothesized interaction stood out as always contributing to more succesful models. That was the inhibition of Gzf3 by Dal80, its close relative. Also, in further selections, hypothesis 2 was also strongly supported, which is the auto-activation of Gat1, probably by binding to its own promoter. On the other hand, models that were missing the hypothesized interactions 1,3, and 5 were the top performers, indicating that these (auto-inhibition of Dal80, inhibition of Dal80 by Gzf3, and cooperative binding by Gln3 and Gat1) are probably not real, or at least significant under the measured conditions.

Lastly, the authors do a bit of model validation by creating new experiments against which to measure model predictions. Using their best model, the expression of Dal80 (Y-axis) under various perturbations is reasonably well-fit.

New experiments support model predictions reasonably well. In this case, the perturbation (a, b) was shifting form poor to rich (glutamine) food source, thereby inducing the repressor regulators such as Dal80, and repressing the glutamine synthetic genes. In c, d, the perturbation was the reverse, moving cells from a rich source to a drug which directly shuts off the signaling of rich conditions, thereby releasing repression.

And given a model, one can isolate individual aspects of interest, such as the predicted occupancy of target promoters/binding sites by the regulatory factors., which they do in great detail. In the end, the authors complain that much remains unknown about this system (give us more funding!). But the far more pressing question is what to do about the thousands of other networks and species with far more complication and less data. How can they be modelled usefully, and what is the minimal amount of data needed to do so?

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