In a previous post I sketched out the importance of frequency normalization in studying the brain, and a possible way to approach the problem. I don’t know if mine is a workable approach- frequency normalization in the brain is a hard problem, due to complex topology and variable state. But comparative frequency analysis within and across brain regions, however we accomplish it, will be really, incredibly important for understanding what’s going on in the brain, and how brains can differ, and maybe even how emotions work. I have a pet theory as to what we’ll find when we’re able to do this sort of frequency analysis in the brain. As with any new theory it’s most likely wrong, but since everybody’s theories on this are similarly disadvantaged (what few big-picture theories are out there), and it’s a topic worth figuring out, I have no qualms about throwing my hat in the ring.
Most importantly, I want to get people thinking about what emotion is, without cop-out references to ‘happiness neurochemicals’ or ‘regions of the brain which control emotion’. When it gets down to it, those are just ways of saying, “we don’t know what emotion is.” For instance, using these poor, correlative explanations of emotion, it would seem we could build a computer that could feel happiness by dumping some dopamine extract on its processor, or make it feel pain by fusing some human nociceptor nerves onto the motherboard. Clearly this is not the case. If we want to deal with emotion at anything except a trivial level, we need to dispense with correlative explanations and move toward an information-theoretic approach, to be able to explain affect in our brains as a special case of more general equations.
So what is emotion? I suggest we look to the mathematics of music theory for a possible answer.
(This is really technical and hypothetical; if you don’t enjoy mathematics and speculative neuroscience and would prefer alternative entertainment, why not check out these captioned pictures of cats instead?)
Lots of very intelligent people are putting lots of effort into mapping the brain’s networks. People are calling these sort of maps of which-neuron-is-connected-to-which-neuron ‘connectomes‘, and if you’re working on this stuff, you’re doing ‘connectomics‘. (Academics love coining new fields of study! Seems like there’s a new type of ‘omics’ every month. Here’s a cheatsheet courtesy of Wikipedia– though I can’t vouch for the last on the list.)
Mapping the connectome is a great step toward understanding the brain. The problem is, what do we do with a connectome once it’s built? There’s a lot of important information about the brain’s connectivity packed into a connectome, but how do we extract it? Read on for an approach to broad-stroke, comparative brain region analysis based on frequency normalization. (Fairly technical and not recommended for a general audience.) Read More
TMS ‘Sonar’ for mapping brain region activity coupling
Modern neuroscience is increasingly suggesting that a great deal of a person’s personality, pathology, and cognitive approach is encoded into which of their brain regions are activity-coupled together. That is to say, which of someone’s brain regions are more vs. less wired together, compared to some baseline, determines much about that person.
Right now such coupling is largely invisible and unquantifiable. If we are to move toward a clearer understanding of individual differences, not to mention psychiatric conditions, it would be invaluable to have a test for this activity coupling. A combination TMS+fMRI alternated pulse device- as it could stimulate a specific brain region/network, and measure how it affected the activity in other regions- may very well provide an objective basis for psychiatric diagnosis and treatment recommendations, and perhaps even a firmer foundation for psychology as a whole.
The following is a somewhat technical writeup of the idea. Not into detailed neuroscience stuff? Click here.
The brain is extraordinarily complex. We are in desperate need of models that decode this complexity and allow us to speak about the brain’s fundamental dynamics simply, comprehensively, and predictively. I believe I have one, and it revolves around resonance.
I’m pretty sure I’ve found the future of medical diagnosis– it’s elegant, accurate, immediate, mostly doctor-less, comprehensive, and very computationally intensive. I don’t know when it’ll arrive, but it’s racing toward us and when it hits, it’ll change everything.
In short– the future of medical diagnosis is to use a gene expression panel along with functional and correlative connections between gene expression and pathology to perform thousands of parallel tests for every single human illness we know of– no matter whether it’s acute, chronic, pathogenic, mental, or lifestyle. In short: one simple test that’ll uncover all health problems.
Exponential advances in gene sequencing technology have produced an embarrassment of riches: we’re now able to almost trivially sequence an organism’s DNA, yet sifting meaning from these genomes is still an incredibly labor-intensive and haphazard task. For instance, consider the following simple questions:
How similar are the genomes of dogs and humans? How does this compare to cats and humans? What about mice and cats? How close, genetically, are mice and corn?
We have all of these genomes sequenced, but we don’t have particularly good and intuitive ways to answer these sorts of questions.
Whenever we can ask simple questions about empirical phenomena that don’t seem to have elegant answers, it’s often a sign there’s a niche for a new conceptual tool. This is a stab at a tool that I believe could deal with these questions more cogently and intelligently than current approaches.
Edit, 3-10-13: The big bang happened. The universe expanded a lot. Everything was pretty evenly distributed. The universe was a uniform mist of plasma, light, and hydrogen, as far as the eye could see.
After 13.77 billion years, things are no longer so evenly distributed. Matter has clumped up into gas clouds, planets, stars, solar systems, galaxies, clusters, superclusters. Quantum fluctuations during the big bang made things a little uneven, and gravity did the rest.
I’ve been trying to figure out how to quantify just how clumped up matter has become. How to put a number on how gravitationally inhomogeneous the universe is. If a universe with a perfectly even mist of atoms and photons is a 1, what are we?
I have this crazy-and-probably-wrong idea that this quantity, and the amount of dark energy observed throughout cosmological history, might share some eerily similar inflection points. Moreover, these two quantities might be causally connected- e.g., an increase in gravitational inhomogeneity may cause an increase in dark energy.
But I don’t think there’s a good holistic calculation of gravitational inhomogeneity yet. And I am not a very good cosmologist.
The following is an attempt to fumble around for an analogy of why this could be the case. However, I ask theorists to focus less on the analogy and more on the simple, empirical prediction that gravitational inhomogeneity and dark energy will correlate better and better as our measurements of them improve.
I like America a lot. But lately I’ve been wondering, “what’s going on here?”
The latest poll numbers are in, and I’m clearly not alone. The AP is now reporting that 81% of Americans think we’re on the wrong track. One need not look far for proximate reasons: a strange and fragile economy, huge credit card debts, the behavior of our elected officials, our election of said officials, the sad, hollow state of our public discourse, voter apathy, the general state of our media, and so forth. There are still plenty of things going right in America, but compared to our particularly exemplary history of competence, principles, and vibrant public life, something has clearly changed.
Working hypothesis: There are substantial arguments from Physics, Physical Chemistry, Biochemistry, Biology, and Entropy that intelligent life could only arise in a universe with exactly three macroscopic spacial dimensions.
If that seems overly technical, I’m taking a stab at the question, “What’s so special about three dimensions? Why don’t we live in four dimensions, or two?”