5 ms·

Novice question: A given dendrite has a voltage raise, presumable because of transmitter from a neighboring neuron. That voltage increase will always be local

Novice question: A given dendrite has a voltage raise, presumable because of transmitter from a neighboring neuron. That voltage increase will always be local unless it is adequate (as it spread and dissipates on its way to the cell body) for an action potential. If they showed an action potential starting at the dendrite, then I would expect it to eventually move to the rest of the cell body and then I wouldn't expect the language about 'not seeing the rest of the cell light up'. So, how did they measure/show actual processing? I'm missing that part.

bl 13y ago
The voltage change (i.e., depolarization) is not strictly local. In some cases, depending on the actual geometry of the dendrite and the particular complement of voltage-activated ion channels, the voltage change as a result of neurotransmitter release might lead to quite a distributed depolarization even without triggering a dendritic action potential. Conversely, an action potential initiated in the dendrites doesn't necessarily faithfully propagate to the cell body (soma). This is also dependent on the local geometry and ion channel distribution. Dendritic action potentials are not all-or-nothing events like those of the axon. To answer your question: Smith, et al., did observe dendritic action potentials (spikes) by measuring a proxy: calcium influx indicated by a fluorescent dye that changes efficiency when bound to calcium. This calcium influx, and by extension, the dendritic spike, is what was spatially-restricted. The authors are extrapolating information processing from the spatially-restricted dendritic spike.
- jasallen 13y ago
  Thanks for the answer. So just to close the loop and make sure I got it, a couple follow ups 'processing' in this case would refer to integrating signals/voltages/neurotransmitters from more than one neighboring neuron? How do they show that this was processing/integrating and not just particular sensitivity to one external stimulus? For 'processing' to be meaningful, would it not have to share the result? In other words propagate the action potential or release neurotransmitter?
  - PeterisP 13y ago
    I'm not a biologist and the parent poster seems to know in far more detail, but from a bunch of neuroscience lectures on how the dentritic spikes travel up to the soma, my takeaway (as a computer guy) was 'hmmm, it looks like a system implemented in FPGA layouts - the geometry features can work as logic gates or delays'; and 'hmmmm, it looks I could design a dendritic tree geometry for almost any boolean function of the inputs, so any computer-chip-like-functionality could be built out of them'. I mean, if I needed (A xor B) and (C or D), then my impression is a single neuron with rather simple geometry and appropriate dendritic connections could calculate that in the sense that this neuron would spike iff the A,B,C,D neurons spiked as required by that formula; but since neurons tend to have much much more connections, then each neuron is technically capable of much more complex calculations, even if many of them in the end do something like 'spike iff any 100+ of my 1000 inputs are spiking'. It's not so simple as that because timing is also relevant, and there were examples of known dendritic structures that do "processing" in terms that a neuron spikes if it receives A slightly before B, but doesn't spike if it receives A slightly after B; so it can be used for detecting motion direction and such.
    - bl 13y ago
      "[I]t looks I could design a dendritic tree geometry for almost any boolean function of the inputs". That's my outlook on the structure-function link between dendritic morphology and dendritic information processing, with the modification that I'd not restrict it to boolean functions. There are very many more types of functions, linear and non-linear, that can conceivably be built out of neuronal dendrites. And I like the nuance of your second paragraph. There are all sorts of wacky, complex calculations one can image being possible, but any one neuron may implement a subset. Now, across a few hundred billion neurons in a mammalian nervous system... You're spot on with regard to timing, too. All this "information processing" with branched dendrites + non-linear ion channels are greatly expanded with a timing component.
      - PeterisP 13y ago
        Well, AFAIK you don't need anything more than boolean functions, since if we're talking about single spikes (not spike frequency), then there either is or isn't a spike, you don't get some spikes larger than other. The linear/nondigital functions IMHO seem to be used as implementation details - for example, a neuron "fire iff 1+ VIP-input fires or 3+ normal inputs fire" can be implemented in wetware by having 'vip-inputs' have thrice as strong synaptic connection, summing all input values in the dendrite, and adjusting so that the firing threshold is appropriate (i.e. a linear function); but in silicon the same thing can (should?) be implemented as a boolean function / logic gates.

bl 13y ago

The voltage change (i.e., depolarization) is not strictly local. In some cases, depending on the actual geometry of the dendrite and the particular complement of voltage-activated ion channels, the voltage change as a result of neurotransmitter release might lead to quite a distributed depolarization even without triggering a dendritic action potential. Conversely, an action potential initiated in the dendrites doesn't necessarily faithfully propagate to the cell body (soma). This is also dependent on the local geometry and ion channel distribution. Dendritic action potentials are not all-or-nothing events like those of the axon. To answer your question: Smith, et al., did observe dendritic action potentials (spikes) by measuring a proxy: calcium influx indicated by a fluorescent dye that changes efficiency when bound to calcium. This calcium influx, and by extension, the dendritic spike, is what was spatially-restricted. The authors are extrapolating information processing from the spatially-restricted dendritic spike.

jasallen 13y ago
Thanks for the answer. So just to close the loop and make sure I got it, a couple follow ups 'processing' in this case would refer to integrating signals/voltages/neurotransmitters from more than one neighboring neuron? How do they show that this was processing/integrating and not just particular sensitivity to one external stimulus? For 'processing' to be meaningful, would it not have to share the result? In other words propagate the action potential or release neurotransmitter?
- PeterisP 13y ago
  I'm not a biologist and the parent poster seems to know in far more detail, but from a bunch of neuroscience lectures on how the dentritic spikes travel up to the soma, my takeaway (as a computer guy) was 'hmmm, it looks like a system implemented in FPGA layouts - the geometry features can work as logic gates or delays'; and 'hmmmm, it looks I could design a dendritic tree geometry for almost any boolean function of the inputs, so any computer-chip-like-functionality could be built out of them'. I mean, if I needed (A xor B) and (C or D), then my impression is a single neuron with rather simple geometry and appropriate dendritic connections could calculate that in the sense that this neuron would spike iff the A,B,C,D neurons spiked as required by that formula; but since neurons tend to have much much more connections, then each neuron is technically capable of much more complex calculations, even if many of them in the end do something like 'spike iff any 100+ of my 1000 inputs are spiking'. It's not so simple as that because timing is also relevant, and there were examples of known dendritic structures that do "processing" in terms that a neuron spikes if it receives A slightly before B, but doesn't spike if it receives A slightly after B; so it can be used for detecting motion direction and such.
  - bl 13y ago
    "[I]t looks I could design a dendritic tree geometry for almost any boolean function of the inputs". That's my outlook on the structure-function link between dendritic morphology and dendritic information processing, with the modification that I'd not restrict it to boolean functions. There are very many more types of functions, linear and non-linear, that can conceivably be built out of neuronal dendrites. And I like the nuance of your second paragraph. There are all sorts of wacky, complex calculations one can image being possible, but any one neuron may implement a subset. Now, across a few hundred billion neurons in a mammalian nervous system... You're spot on with regard to timing, too. All this "information processing" with branched dendrites + non-linear ion channels are greatly expanded with a timing component.
    - PeterisP 13y ago
      Well, AFAIK you don't need anything more than boolean functions, since if we're talking about single spikes (not spike frequency), then there either is or isn't a spike, you don't get some spikes larger than other. The linear/nondigital functions IMHO seem to be used as implementation details - for example, a neuron "fire iff 1+ VIP-input fires or 3+ normal inputs fire" can be implemented in wetware by having 'vip-inputs' have thrice as strong synaptic connection, summing all input values in the dendrite, and adjusting so that the firing threshold is appropriate (i.e. a linear function); but in silicon the same thing can (should?) be implemented as a boolean function / logic gates.