Neuron Simulation, notes

Approaches, which, in turns, following out three branches of exploratory science:

• Experimental,
• Theoretical
  1. Informatics neuroscience (looking at trend, correlations and patterns in data),
  2. Theoretical neuroscience (explaining the data and predicting
  3. Computational neuroscience (creating minimal model that fit specific experimental data),
  4. Applied neuroscience (using neurosciences in medicine and engineering by notably building machine to see how the neurons work)
• & Simulation (or lqqd that this course is about).

Principles:

• Dense reconstructions (it's about an ordered system so, opposite than it were about a random system) it's assumed to get done algorithmically (the smallest data set with & the [algorithm|s] which [rule|s] over).
• Bottom-up reconstructions,
• Iteratively reconstructions & test.

I am going to track this exploration on the subject on a handful of idea tools as keystrokes, connections | flows & systems | circuits.

• So, my first annotation here is the flow in which this approach about neuron as a whole is on, ion channels, synapses & neuron circuits.
• Now lets track the info source in terms of simulation so we can control also the replication method (rationale & the complexion itself got made)
  • ion channel channel screening, biophysical screening so the explore the biophysics of these channels.. implying kinetics (open closed) of the channels, its distribution, combination, conductance, so modelling the ion channel, its morphology and | or its electrical behaviour,
  • neurons paired recordings, staining the two..
  • n. circuits antibody staining, in situ hybridization,

The question quiz here is indeed my point when defining the keystroke specially about (simulating) neuron.

— What is, in your opinion, the main challenge in mining of existing knowledge on the brain. I feel the keystroke about mining is the coding language we opted to interpret the data and build to simulations. As a programming language is necessary, the question easily gets deviation to the interface or media used itself, its virtues, shortcomings and so on. Especially if researchers are previously versed in any of them. I do not think this fact were intrinsic wrong, researchers should be able to explain their approaches within plenty of comfort zones. However this fact triggers at least two inconveniences: First, it narrows the replication, or, the result evaluation or, lets also call it, the discussion phase, into groups based on the language media used to expose the results or its eventual approaches. How many times me myself, as student or, just as, an intelligent plain man interested in the field have had to just observe what exposed and without ability to replying because of the programming language barrier. So that as soon as you decide to get levelled-enough literacy to, in turn, get into that specific discussion some more interactive, reply based on whatever different language tool there were out, shows up. So that, the easy route this question ends up is a kind of school of exposition problem.

A second inconvenience is the virtues of the media or language in question itself. A lot of discussions as I found got suck as function of packages used to expose approaches.

I think we have to agree in a kind of standard, a kind of pseudo code as a default language so that any researcher were able to replicate results.

• Hey, —mmm… —when, a kind of, positive difference, should not be considered an advantage, is that like, as I should get it rendered this, kind of, dissonance? Look at this question [ref: week1, practice quiz :reconstruction strategies] or is it just another issue for my WTF series collection?

Let's list some of them.

• critical data may be missing
• biological data has a lot of mistakes (actually there are much more mistakes than accurate data)
• there are a lot of disciplines involved (which is not a caveat, really, though it get things complicated, critically complicated, actually).

  

Basically in search of: IR-DC microscope,

• its electrical profile
• morphological profile,
• molecular profile.

Hey, following a crash course on #mozillaNetwork projects I run out with this by itself gorgeous tools: The brain box and Cytoscape a graph JS library useful as we are here trying to perform visual simulation, so let's check for it later in this course.