[ExI] another step towards uploading
rafal.smigrodzki at gmail.com
Fri Oct 4 04:11:27 UTC 2013
On Wed, Oct 2, 2013 at 5:49 AM, Anders Sandberg <anders at aleph.se> wrote:
> On 2013-10-02 05:05, Rafal Smigrodzki wrote:
>> A technique capable of directly reading nanoscale molecular
>> distributions of multiple molecular species (a prerequisite for
>> individual brain physiology reconstruction) is the holy grail of brain
>> uploading. Near-field MRS could be it, perhaps.
> I wonder how much and what information is actually needed to deduce synapse
> types. Obviously, just cataloging the local chemical species would give a
> ground truth. But we also know vesicle size and electron density gives about
> a bit of information (roughly, excitatory or inhibitory). Voltammetry
> reveals levels of dopamine, serotonin and noradrenaline. No doubt other
> markers indicate other properties, likely in a noisy and overlapping manner.
> But from a machine learning perspective, if we had good data sets of
> multimodal data we could try training classifiers that could tease out a
> proper decision tree. Comparing with real ground truth is of course
> essential, so we need a "chemical dissection method" for synapses to use as
> test set. But I suspect that in the end we will end up with surprisingly
> simple statistical models.
### I think you are right about the simple statistical models
substitutable for large chunks of dendritic trees but I would expect
that the translation from a physical description of a neuron to a
simplified equivalent might be very complex. There is a fair amount of
analog computation going on in the dendritic trees, where the shape of
the tree and the precise relative location of synapses modify the
summation of inputs from synaptic strengths. After neural scan you
would have to do some very heavy brute-force computations to yield the
simplified models. All should be doable though, as long as the scan is
of sufficient quality.
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