Lost Thoughts in the Wake-Sleep Transition

I’ve been meaning to write about this curious phenomenon I experience every time I go to sleep. Lying in bed last night, I was thinking about a movie I had just finished watching – The Aviator, a great movie! – and was overcome by a sudden frustration: some idea that was running through my mind had simply vanished, to be replaced by something silly and mundane. Trying desperately to remember what I had just been thinking about, I could find no trace of my thoughts. It was as if they were never recorded. This happens several times, until I finally give up and fall asleep. Even more perplexing is that I am aware of those lost thoughts, I know something is missing. I just can’t remember what it was.

If these aren’t freak phenomena, one can imagine something in the awake-sleep transition that messes with short term memory. It’s as if whatever network or assembly representing the would-be memory doesn’t undergo short term plasticity necessary to “solidify” those connections. This is of course overly simplistic and probably misleading language, but a way to think about it. Perhaps this can (or has been?) analyzed in rats, as in the “replay” or reactivation activity in hippocampus of experienced events, during sleep, as in this paper by Matt Wilson of MIT. One could examine lost thoughts in the awake-sleep transition by looking at the temporal structure of activity during that transition vs. same activity during experience on a maze, for example. Perhaps this loss of thought depends on some subcortical “kick” that’s absent during sleep. Just a thought.

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The Daily Show aired a special report by Aasif Mandvi on “an expensive lesson about bringing fish back to life,” or the dangers of leaving children with the capability to make purchases on the Apple App Store. The point of this story is that children can’t inhibit behavior as well as adults can due to their underdeveloped frontal cortices; and are therefore vulnerable targets to those whose sole purpose is to make easy money, not unlike drug dealers selling to addicts who just can’t help themselves:

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Christopher Hitchens writes in the January edition of Vanity Fair about what he believes to be a nonsensical maxim: “What doesn’t kill me, makes me stronger.” Hitchens is suffering from esophageal cancer, the primary reason for the sentiment that he is not becoming “stronger,” but is rather on a terminal decline.

The phrase is attributed to Nietzsche, whose mental decline late in life, Hitchens notes, probably did not make him any stronger. Nor did the philosopher Sydney Hook consider himself stronger after a terrible experience in a hospital. Hitchens considers himself to be among the many who don’t conquer illness to come out stronger. But there is a flaw in this reasoning – the first condition to becoming stronger is to not be killed. Hitchens is thankfully still alive and kicking (i.e. writing), but he hasn’t defeated his cancer (yet, hopefully); it is only after the cancer is over with that Hitchens can say he’s stronger or weaker. Now is premature. The more important qualification is that “stronger” should mean mentally stronger, not physically. Diseases that target the mind specifically, like Nietzsche’s syphilis, should be discounted; all others should hopefully be an exercise for the power of will and mental fortitude.

Whenever you think life is hard, remember Hitchens and countless others who brave horrible diseases. Stay stark, Hitch!

Hitchens’s essay may be found here.

Science, Religion and Values: Magisteria Redefined

Science and religion have been archenemies for some time now, with one on a quest for knowledge and truth, and the other seeking to fill a perceived void of meaning in lives. Logical inspection confirms the two systems are incompatible with one another, since science requires evidence for all claims, whereas religion insists on faith when there is no evidence whatsoever. But many do have both science and religion in their lives. How do they deal with the conflict? Stephen Jay Gould wrote in a 1997 essay on the non-overlapping magisteria, NOMA, that there actually is no conflict between science and religion:

“No such conflict should exist because each subject has a legitimate magisterium, or domain of teaching authority—and these magisteria do not overlap (the principle that I would like to designate as NOMA, or “nonoverlapping magisteria”).

The net of science covers the empirical universe: what is it made of (fact) and why does it work this way (theory). The net of religion extends over questions of moral meaning and value. These two magisteria do not overlap, nor do they encompass all inquiry (consider, for starters, the magisterium of art and the meaning of beauty). To cite the arch cliches, we get the age of rocks, and religion retains the rock of ages; we study how the heavens go, and they determine how to go to heaven. Continue reading

Brainy Computers

“We’re not trying to replicate the brain. That’s impossible. We don’t know how the brain works, really,” says the chief of IBM’s Cognitive Computing project, which aims to improve computing by creating brain-like computers capable of learning in real-time and consuming less power than conventional machines. No one knows how the brain works, but have the folks at IBM tried to figure it out?

It seems strange to say that it’s impossible to replicate the brain, especially coming from a man whose blog‘s caption reads, “to engineer the mind by reverse engineering the brain.” Perhaps I’m picking at his words – replicating and reverse engineering are totally different things; to replicate is to copy exactly, while reverse engineering isn’t as strict, since it’s concerned with macroscopic function rather than microscopic structure. But of all the things that seem conceptually impossible today, it’s the “engineer the mind” that’s the winner, especially if one can’t “replicate the brain.” The chances of engineering a mind are greater the closer the system is to the brain; that’s why my MacBook, to my continual disappointment, does not have a mind.

These little trifles haven’t stopped Darpa from funding IBM and scientists elsewhere. IBM now boasts a prototype chip with 256 super-simplified integrate-and-fire “neurons” and a thousand times as many “synapses.” This architecture is capable of learning to recognize hand-drawn single-digit numbers. Its performance may not be optimal, but still impressive considering the brain likely allocates far more neurons (and far more complicated neurons) to the same task. On another front, the group reported using a 147,456-CPU supercomputer with 144TB of main memory to simulate a billion neurons with ten thousand as many synapses. Now if only they could combine these two efforts and expand their chip from two hundred to a billion neurons.

Dancing for Science

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Science is difficult to understand and even more difficult to explain. John Bohannon thinks that words are inept at explaining scientific concepts, and should stay out of the way. Powerpoint is useless too. Instead, Bohannon argues, scientific concepts should be explained with dance. He foresees a boost to the economy if dancers were to be hired as aids to presenters, not only because those dancers would have jobs, but because science would be communicated more effectively, leading to more innovation.

Bohannon presents these ideas in an engaging TEDx talk, with the help of the Black Label Movement dance team.  No doubt, seeing people dance out cellular locomotion is fun and more straightforward than hearing a verbal description of the same thing. I wonder though if such concepts would be more accurately portrayed and easier to understand through animations. Perhaps there is something about seeing people perform live that is more engaging than seeing animations or the same performance on a screen. If that’s true, then having dancers at one’s presentations would be very helpful (it would also make that presentation stand out, if no one else has dancers).

 

 

Descriptive vs. Predictive Models

When we look back at the important advances in neuroscience in the 20th and 21st centuries, what will we remember? What will we still find useful and worth pursuing further? The field is still in its nascent stages, even a century after Ramon y Cajal showed evidence for the neuron doctrine, establishing the neuron as a fundamental unit of the nervous system; and Brodmann published his cytoarchitecture studies that convinced the world that the brain is divided into distinct areas and likely uses those to divvy up processing. Yet we still have virtually no clue how the brain works: there is no central theory, no cures for brain diseases; only a whole lot of curious, enthusiastic and optimistic minds and some funding to help them get stuff done.

And it is rightly so that some neuroscientists have serious physics Continue reading

Whale Song Analysis Crowd-sourcing

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Scientific American is collaborating with marine scientists on a project to crowd-source analysis of whale songs and calls. Having gathered thousands of sound files from many species of whales, scientists now need to classify each call and song to get an understanding of each specie’s repertoire. Once the calls and songs are sorted and classified, scientists can pursue interesting questions like, is a whale’s song repertoire related to its intelligence?

To classify the vocalizations, scientists are asking the public for help. On whale.fm, anyone (no expertise required) can sift through some spectrograms and embedded sound files, and match them to a template. It’s easy, fun and cool. Something that would take one person months or years to do, can now by accomplished much faster by the public in a fun format.

Some previous efforts in scientific crowd-sourcing like FoldIt, a game in which people fold proteins based on simple rules (computers can’t do this), or the search for new galaxies by amateur astronomers from images taken by the Hubble telescope. Perhaps this type of effort could help the Connectome efforts to map out the brain down to each synapse using electron microscopy, where every neurite in a cross-sectional image must be strung to itself in adjacent images. Tracing axons across thousands of EM images could actually make a fun and productive game.

What are experts for?

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It is by no mistake that philosophers from Plato to Hume to Adam Smith have advocated a division of labor as a driving force of society and its economy. The more specialized one’s labor, the more advanced the resulting product. As people gain expertise in their distinct fields, the more they are able to advance those fields. This is as true for labor as it is for science (in general; there is a lot to be said for multi- and cross-disciplinary approaches and out of the box thinking that specialization usually dampens. But on the whole,  it is undoubtedly more advantageous to specialize in a field than not). Scientific experts are people society relies on to advance knowledge and establish facts; they are the people we go to when we need answers.

Here is why we need experts: Bret Stephens is a journalist and  Wall Street Journal columnist whose training is, supposedly, in journalism and maybe economics (Wikipedia, which never lies, says he attended the London School of Economics). In his column today, Bret Stephens writes about global warming. Entitled “The Great Global Warming Fizzle,” the article compares climate change science to a religion – and a dying one too – whose adherents are “spectacularly unattractive people” and whose “claims are often non-falsifiable, hence the convenience of the term ‘climate change’ when thermometers don’t oblige the expected trend lines.”

Now if Bret Stephens were an environmental scientist with proper training, his criticism of climate science would be worth hearing. But just as we don’t take physics advice from members of the Taliban (Sam Harris’s favorite example), we shouldn’t take climate change advice from Bret Stephens. Has he seen the data in question? Would he know how to interpret it? Would he draw the same conclusion if money and government intervention were not factors? The worry is that he is not fulfilling his role of journalist, in which he is expected to provide fair interpretations of the science and policy to the public, who are not experts. Instead of facts, we get an opinion piece on something Bret Stephens has no expertise in.

Here’s the dilemma for those who care – is it better to ignore the vocal people who don’t know what they’re talking about or to correct them and spread the correct message? The latter would be a far more active and constructive choice, but it should have to be a proactive message instead of reactive as in this post.

Not Another Rodent

Slate magazine had a slideshow by Daniel Engber a little more than a week ago on unusual laboratory animals and why they’re important. The slideshow was prompted by Engber’s observation that mice and rats make up an enormous proportion of all lab animals, perhaps limiting what we can conclude from experimental results and narrowing our perspective on what questions to ask. In short, scientists need to start thinking outside the box when it comes to model organisms. Engber lists fourteen animals, some of which have already given important clues to specific questions. I will mention some of those here.

1. The squid: the squid peaked in importance in the 1950′s, when Hodgkin and Huxley got the idea to use its giant axon (up to 1mm diameter) to study properties of the action potential. The large diameter made it possible for them to insert micro-electrodes directly into the intracellular space of the axon, thereby measuring the flow of ions across the membrane during various stages of the action potential or under different extracellular ionic concentrations. This work resulted in Hodgkin and Huxley’s mathematical model of AP generation, which earned them the 1963 Nobel Prize. Continue reading