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I would say the title alone kept me away from reading it. And this is coming from a person that worked in systems neuroscience and machine learning for a decade

I would say the title alone kept me away from reading it. And this is coming from a person that worked in systems neuroscience and machine learning for a decade. The scientific community (at least the neuroscience and atmospheric science I know about) does itself few favors with the manner it writes. Orwell's essay on politics and the english language comes to mind: https://www.orwellfoundation.com/the-orwell-foundation/orwell/essays-and-other-works/politics-and-the-english-language/ https://www.orwellfoundation.com/the-orwell-foundation/orwel...

bubblyworld 2y ago
Is your objection to the title just political, or does it have red flags for you on the science front? From the outside, it seems like an interesting thing to do to me (incorporating spatial stuff into a kind of neural network, I mean). But I don't know enough neuroscience to know if that's even a sensible thing to do haha.
- alan-hn 2y ago
  The spacial characteristic is important because activity at two nearby dendrites receiving excitatory (or inhibitory) inputs have an additive effect which is greater the closer they are, this is because the signal is based on concentration of ions and when those signals are closer together they can surpass the concentration threshold that's needed to trigger voltage gated ion channels to open.
  - bubblyworld 2y ago
    Interesting, thanks for the basics. That makes sense - I'm a bit confused about how inhibition vs excitation works if they're both based on ion concentration (is it like positive vs negative ions, or a different mechanism entirely?), but I'll do some googling!
    - alan-hn 2y ago
      Different ions with different charges. Sodium (Na^+) as you can see has one positive charge per ion, as does potassium (K^+), calcium has two (Ca^2+), and hydrogen has one (H^+). This charge is balanced with negative charges, a minority from chloride (Cl^-) and the majority from proteins. When it comes to proteins, they are comprised of amino acids which have varying charges and proteins generally end up with a negative charge from all of the sites where they can be protonated. Just for clarification, protonation is where a H+ (a proton) can ironically bind to a molecule with a negative charge, this is how most acids work (that's a generalization don't @ me, chemists) So we have a shitload of proteins inside the cell with a shitload of negative charges, we have a variety of ions with positive charges, and we have ion channels which are transmembrane proteins that have a specific structure to allow certain ions of one charge or size or just all ions in general to pass through their pore. Some are leak channels which are almost always open, some open when a ligand (other molecule) binds, some open when they sense a certain voltage. That takes us to difference in charge. The cell membrane acts as a capacitor, separating charge. There are many pumps that pump out positive ions to maintain this separation and different cells can sit at different voltages where the voltage is simply the difference in charge between the intracellular and extracellular space, this can be measured in whole cell configuration patch clamp experiments where we attach a pipette with a tip smaller than a cell to the membrane and apply suction to break into the cell so we can get a reading but that's a whole topic on its own When it comes to excitation vs inhibitions, it really is about positive vs negative charges. Excitatory ion channels such as kainate AMPA and NMDA receptors pass cations, the positive ions, while GABAa and glycine receptors are ion channels that selectively allow Cl^- into the cell in adults. The developing brain is weird and backward when it comes to Cl^- so again, another topic
      - bubblyworld 2y ago
        Wild, that's really complicated. A bit of a tangent, but one takeaway for me there is that neural nets are _far_ more dissimilar to brains than I thought. Sounds like a lot more going on than "signals add up to threshold"!
        2y ago
robwwilliams 2y ago
I do not understand the comment regarding the title. Strikes me as neutral and descriptive. Delighted to see sets of neuromorphic approaches used in more sophisticated compartmental models. And modeling well understood directional selectivity is a rational place to start.

bubblyworld 2y ago

Is your objection to the title just political, or does it have red flags for you on the science front? From the outside, it seems like an interesting thing to do to me (incorporating spatial stuff into a kind of neural network, I mean). But I don't know enough neuroscience to know if that's even a sensible thing to do haha.

alan-hn 2y ago
The spacial characteristic is important because activity at two nearby dendrites receiving excitatory (or inhibitory) inputs have an additive effect which is greater the closer they are, this is because the signal is based on concentration of ions and when those signals are closer together they can surpass the concentration threshold that's needed to trigger voltage gated ion channels to open.
- bubblyworld 2y ago
  Interesting, thanks for the basics. That makes sense - I'm a bit confused about how inhibition vs excitation works if they're both based on ion concentration (is it like positive vs negative ions, or a different mechanism entirely?), but I'll do some googling!
  - alan-hn 2y ago
    Different ions with different charges. Sodium (Na^+) as you can see has one positive charge per ion, as does potassium (K^+), calcium has two (Ca^2+), and hydrogen has one (H^+). This charge is balanced with negative charges, a minority from chloride (Cl^-) and the majority from proteins. When it comes to proteins, they are comprised of amino acids which have varying charges and proteins generally end up with a negative charge from all of the sites where they can be protonated. Just for clarification, protonation is where a H+ (a proton) can ironically bind to a molecule with a negative charge, this is how most acids work (that's a generalization don't @ me, chemists) So we have a shitload of proteins inside the cell with a shitload of negative charges, we have a variety of ions with positive charges, and we have ion channels which are transmembrane proteins that have a specific structure to allow certain ions of one charge or size or just all ions in general to pass through their pore. Some are leak channels which are almost always open, some open when a ligand (other molecule) binds, some open when they sense a certain voltage. That takes us to difference in charge. The cell membrane acts as a capacitor, separating charge. There are many pumps that pump out positive ions to maintain this separation and different cells can sit at different voltages where the voltage is simply the difference in charge between the intracellular and extracellular space, this can be measured in whole cell configuration patch clamp experiments where we attach a pipette with a tip smaller than a cell to the membrane and apply suction to break into the cell so we can get a reading but that's a whole topic on its own When it comes to excitation vs inhibitions, it really is about positive vs negative charges. Excitatory ion channels such as kainate AMPA and NMDA receptors pass cations, the positive ions, while GABAa and glycine receptors are ion channels that selectively allow Cl^- into the cell in adults. The developing brain is weird and backward when it comes to Cl^- so again, another topic
    - bubblyworld 2y ago
      Wild, that's really complicated. A bit of a tangent, but one takeaway for me there is that neural nets are _far_ more dissimilar to brains than I thought. Sounds like a lot more going on than "signals add up to threshold"!
      - 2y ago

robwwilliams 2y ago

I do not understand the comment regarding the title. Strikes me as neutral and descriptive. Delighted to see sets of neuromorphic approaches used in more sophisticated compartmental models. And modeling well understood directional selectivity is a rational place to start.