Mary’s room

Mary’s room is a philosophical thought experiment used to question a physical or materialistic explanation of consciousness and mind.  The argument has various forms but it essentially boils down to a situation where Mary is a scientist who cannot see colours but goes about to study everything physical there is to know about colour.  So she learns about light, quantum mechanics, molecular biology, photoreceptors, neuroscience, psychology, art, and so forth.  Then suddenly her colour vision is restored.  The question then is whether or not she has learned something new.  If you answer yes, then there cannot possibly be a physical or material explanation of consciousness since she has learned everything that she could about the physical properties of colour vision.  The thought experiment is meant to highlight that there seems to be something special and nonphysical about qualia.

I’m certain that most everyone has at one  point wondered if what they call red looks the same to someone else.  How many times have you had a conversation where someone says “How do I know that my red is not your blue?”  The philosopher David Chalmers uses Mary’s room as one of his arguments against a pure physical explanation of consciousness.  I believe he is the person who coined the term “the hard problem of consciousness”, for the issue of how to understand the awareness of consciousness.  His arguments are quite compelling but I haven’t quite jumped off the materialistic bandwagon.  My response to Mary’s room is that if Mary truly discovered everything to know about consciousness then she will not learn anything new when her colour vision is restored.  However, I might differ from other materialists in that I believe that she would have to simulate colour vision in her brain to qualify as knowing everything physical because there is a profound difference between knowing what an algorithm is and actually executing it.  The reason, which drives much of my recent philosophical inquiry, is the Halting Problem.

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New paper on TREK channels

This paper came out of a collaboration instigated by my former fellow Sarosh Fatakia.  We applied our method using mutual information (see here and here) to a family of potassium channels known as TREK channels.

Structural models of TREK channels and their gating mechanism

A.L. Milac, A. Anishkin, S.N. Fatakia, C.C. Chow, S. Sukharev, and H. R. Guy

Mechanosensitive TReK channels belong to the family of K2p channels, a family of widely distributed, well-modulated channels that uniquely have two similar or identical subunits, each with two TM1-p-TM2 motifs. Our goal is to build viable structural models of TReK channels, as representatives of K2p channels family. The structures available to be used as templates belong to the 2TM channels superfamily. These have low sequence similarity and different structural features: four symmetrically arranged subunits, each having one TM1-p-TM2 motif. Our model building strategy used two subunits of the template (KcsA) to build one subunit of the target (TREK-1).  Our models of the closed channel were adjusted to differ substantially from those of the template, e.g., TM2 of the second repeat is near the axis of the pore whereas TM2 of the first repeat is far from the axis.  Segments linking the two repeats and immediately following the last TM segment were modeled ab initio as α-helices based on helical periodicities of hydrophobic and hydrophilic residues, highly conserved and poorly conserved residues and statistically related positions from multiple sequence alignments. The models were further refined by 2-fold symmetry-constrained MD simulations using a protocol we developed previously. We also built models of the open state and suggest a possible tension-activated gating mechanism characterized by helical motion with 2-fold symmetry. Our models are consistent with deletion/truncation mutagenesis and thermodynamic analysis of gating described in the accompanying paper.

 

 

addendum: link fixed

Linear Regression

As someone who was trained in nonlinear dynamics, I never gave much thought to linear regression.  After all, what could be more boring than fitting data with a straight line.  Now I use it all the time and find it rather beautiful.  I’ll start with the simplest example and show how it generalizes easily.  Consider a list of N ordered pairs (x_i,y_i) and you want to fit a straight line through the points. You want to find parameters such that

y_i = b_0 + b_1 x_i +\epsilon_i   (1)

has the smallest errors \epsilon_i where  smallest usually, although not always, means in the least squares sense.

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Brain emulation

The podcast Econtalk featured eclectic economist and blogger Robin Hanson last week. The discussion was on the Singularity, which I posted on here.  Hanson’s take on the Singularity is less mystical than usual. He notes that the global economic growth rate, which he equates with the human population growth rate, has had a few punctuated events that can be considered to be singularities. The first was the arrival of humans, the second was the advent of agriculture and the third was the industrial revolution. Currently, we are doubling economic activity every 15 years. The historical increase in growth rate is a factor of 200 at each singularity. From this he predicts that after the next singularity the economic doubling time will drop to two weeks So if you put a penny in the bank, you’ll be a millionaire after a year. He examines what sorts of technological advance would get growth rates like this and concludes that artificial intelligence (AI) that can improve itself is the only plausible source. This would actually be a second order effect since humans are already possess a biological intelligence that can improve itself.
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2011 JMM talk

I’m on my way back from the 2011 Joint Mathematics Meeting.  I gave a talk yesterday on finite size effects in neural networks.  I gave a pedagogical talk on the strategy that Michael Buice and I have employed to analyze finite size networks in networks of coupled spiking neurons.  My slides are here.  We’ve adapted the formalism we used to analyze the finite size effects of the Kuramoto system (see here for summary) to a system of synaptically coupled phase oscillators.

Podcast update

Here’s whats on my iPod these days.  I definitely try to listen to the following three each week.  They are all about an hour so they fit into my drive home from work.

Quirks and Quarks:  Canadian Broadcasting Corporation’s weekly radio science show.  I used to listen to it as a child.  The first host was former scientist and current environmentalist David Suzuki.  It is now hosted by Bob McDonald.

The Science Show:  This is Australia’s long running radio science show hosted by the inimitable Robyn Williams

Radio Lab:  Possibly the most innovative thing ever on radio.  If you’ve never listened to radio lab, your missing out on a fantastic experience.

I sometimes listen to these.  The philosophy shows are half an hour or shorter while Econtalk is often longer than an hour so they are not as convenient to listen to on my drive.

Philosopher’s Zone: A show that is probably only viable in Australia, which has a vibrant philosophical community.  Host Alan Saunders is also a food expert.

Philosophy Bites: These are usually quite short but informative

Econtalk: Salon-like conversations between George Mason economist Russ Roberts and a guest covering a wide range of topics in economics and beyond  Although Roberts is a self-professed believer in markets his show is fairly well-balanced with different viewpoints.

I used to listen to these shows more but find myself dialing them up less for some reason these days:

All in the mind:  I find this half hour radio show a little too melodramatic at times but it can be interesting

The Naked Scientists:  This is a very popular radio show/podcast out of Cambridge, England.  I find it a little too flip at times and the hosts sometimes make mistakes.

In addition to these regular podcasts, I also listen to university lectures, mostly in philosophy, available on iTunes U.