The classic philosophical dilema of Neuroscience found its way to XKCD
As the initiative of my significant other, we attended the public event called – “Stem Cell Treatments, where are we? – A focus on Neurological Disease”.
The title is quite descriptive. The aim was to present the stem cell research to the general public, focussing on the application in the neurological diseases.
I have to say the event was both very well organised and gave me an insight into the aspects of the Neuroscience I am very weak at – applications in health.
I am especially excited about this one. The work of Michael Häusser and his lab is quite influential in my PhD. Let’s see how this goes …
It turned out I wasn’t quite able to blog as he talked. One reason was the fact that the talk was really interesting and my brain couldn’t really follow it and write at the same time. Second reason is my loud laptop fan, which was driving everybody else crazy.
So here you have the post-mortem abridged version, full of my subjective views and links to what I am generally thinking of doing during the course of my PhD.
The above is a title of a discussion at the interdisciplinary ‘Philosophy, Psychology, and Informatics Reading Group’. We have
Matteo Colombo and Matthew Chalk discussing two recent papers on two theoretical approaches to cognitive modelling:
Griffiths, Thomas L. et al. 2010. “Probabilistic models of cognition: exploring representations and inductive biases.” Trends in Cognitive Sciences 14(8): 357-364.
McClelland, James L. et al. 2010. “Letting structure emerge: connectionist and dynamical systems approaches to cognition.” Trends in Cognitive Sciences 14(8): 348-356.
I was lucky enough to get a chance to listen to Daniel Dennett, one of those philosophers who have their own Wiki page. He is interested in cognitive science, free will, very much pro-evolution and atheism. According to this wiki page he is also a Compatibilist, which as I learned just now is a label for someone who believes that free will and determinism are compatible. And a big part of his talk was dedicated to this topic.
Way back when, he already wrote a book with an ambitious title Consciousness_Explained (I am still reading it). Besides being simply ambitious, such title sweeps every decent neuroscientist off of his feet. An indirect provocation.
The title of the talk saying “When Neuroscientists think they can do Philosophy” was enough of a direct provocation to fill the large lecture room of 400+ sits even when the tickets were not free. And there were people who didn’t get in. And there was someone leaving the talk after 15 minutes loudly saying something along the lines – “Bullshit, I have better things to do in my life.” All the signs of a good talk about to happen.
December 09 – 10, 2010 – Université Pierre et Marie Curie, Institut Henri Poincaré – Homepage
What coding strategy brain uses? Are the timings of spikes important (temporal coding), or simply the number of spikes in a given time window is sufficient information carrier (rate coding)? For sure the former is faster and more efficient and the later is more reliable and robust. There are many papers showing evidence for one or the other.
Most likely brain is not all that picky and simply uses whatever is more appropriate for the task, so I would hypothesise that different brain areas employ different strategy and possibly can even switch between the two depending on the task (this is a bit of a wild statement).
I will use this place to gather the references to the studies making claims towards one or the other (or possibly yet other) coding strategy in the brain.
Initially I was told and thought that the computations in the brain are done by the networks of neurons. Reading the O’Reilly and Munakata book Explorations in Cognitive Neuroscience this is achieved by imagining neurons as points (nodes) connected to each other. The connections are simple directed weights, can have positive or negative values and can change. They determine the amount of signal being passed from one node to another. Already such setup can perform complex computations. Good, this works for sure.
Biology is bit more complex, though. Neurons are not points, they differ greatly one from another, there are several types, … Commonly though they all have dendrites. Mostly they have receptors catching the signals from other neurons (this is always the case for interneurons). And they are a complex network themselves! They have several branches, which normally all end up in the soma (neuron body). Based on what rolls down to the soma, the neuron either fires an action potential and sends the signal forward to the next set of neurons.
Now we finally come to the question. Are those dendrites simply collecting the signals coming from other neurons and summing it all up in soma (being integrators), or they actually do some computations on their own? To get deeper into that, check the review by London and Häuser called Dendritic computation (not too hard to guess what they think about it, huh?). In this way, the dendrites could somehow be the neurons inside the neurons and would thus make the whole network extra complex and extra capable of fast computations. But at the same time, complexity creates vulnerability, so we need to make sure the system stays robust.
Anyway, here is the question, let’s get at it!
Welcome to Progress log. This is a place where I put out ideas that I work on during my research (currently a PhD). Feel free to look around and comment. Oh yes, not everything is public.