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Phasic firing in vasopressin cells: understanding its functional significance through computational models.

MacGregor DJ, Leng G - PLoS Comput. Biol. (2012)

Bottom Line: By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input.Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response.These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.

View Article: PubMed Central - PubMed

Affiliation: Centre for Integrative Physiology, University of Edinburgh, Edinburgh, United Kingdom.

ABSTRACT
Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.

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Comparing the population spike response of phasic and non-phasic model cells.Data here is from a population of 100 identical model cells (using the fit to cell v1) run in parallel, taking as output the summed spike rate. Synaptic input uses a common rate parameter, Ire, but was generated independently for each neuron, maintaining an asynchronous population. Non-phasic cells use gL = 0. To test pulse response, Ire, was set to a defined pulse input for 1s at four time points spaced 100s apart. The pulse response was measured as the mean population spike rate response over the four pulses. (A) Mean population rate with a varied base input rate (range 100–1000). The population response in the phasic cells, shows a much more linear relation to the input, once input is sufficient to trigger phasic firing, particularly in the physiological spiking range of 1–8Hz. (B) Population spike activity in non-phasic and phasic cells with matched 500Hz base input rate and 1000Hz pulse input. The summed asynchronous bursting activity in the phasic cells does not show the bursting, but does show more variable activity and a lower mean spike rate. Each input pulse produces a distinct increase in firing rate. (C) Testing response with a varied base input rate (range 100–1000) and fixed 1000Hz pulse input. As background input increases, the mean pulse response in the non-phasic cells gradually falls, whereas in the non-phasic cells it is much more consistent. (D) Testing response with varied pulse input rate (range 100–1000Hz) and base rate set to give matched mean firing rate = 5 spikes/s (non-phasic base Ire = 255, phasic base Ire = 560). The phasic population response shows a much more linear relation to the input pulse rate.
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pcbi-1002740-g009: Comparing the population spike response of phasic and non-phasic model cells.Data here is from a population of 100 identical model cells (using the fit to cell v1) run in parallel, taking as output the summed spike rate. Synaptic input uses a common rate parameter, Ire, but was generated independently for each neuron, maintaining an asynchronous population. Non-phasic cells use gL = 0. To test pulse response, Ire, was set to a defined pulse input for 1s at four time points spaced 100s apart. The pulse response was measured as the mean population spike rate response over the four pulses. (A) Mean population rate with a varied base input rate (range 100–1000). The population response in the phasic cells, shows a much more linear relation to the input, once input is sufficient to trigger phasic firing, particularly in the physiological spiking range of 1–8Hz. (B) Population spike activity in non-phasic and phasic cells with matched 500Hz base input rate and 1000Hz pulse input. The summed asynchronous bursting activity in the phasic cells does not show the bursting, but does show more variable activity and a lower mean spike rate. Each input pulse produces a distinct increase in firing rate. (C) Testing response with a varied base input rate (range 100–1000) and fixed 1000Hz pulse input. As background input increases, the mean pulse response in the non-phasic cells gradually falls, whereas in the non-phasic cells it is much more consistent. (D) Testing response with varied pulse input rate (range 100–1000Hz) and base rate set to give matched mean firing rate = 5 spikes/s (non-phasic base Ire = 255, phasic base Ire = 560). The phasic population response shows a much more linear relation to the input pulse rate.

Mentions: To study population response, we compare the summed activity of 100 model cells in two conditions: one where all cells were made phasic by setting gL = 8.5, and one where the cells were made non-phasic by setting gL = 0, but with no other change (Figure 9). To maintain an asynchronous population, we use independently generated input PSPs for each model cell, using a common input rate, parameter Ire.


Phasic firing in vasopressin cells: understanding its functional significance through computational models.

MacGregor DJ, Leng G - PLoS Comput. Biol. (2012)

Comparing the population spike response of phasic and non-phasic model cells.Data here is from a population of 100 identical model cells (using the fit to cell v1) run in parallel, taking as output the summed spike rate. Synaptic input uses a common rate parameter, Ire, but was generated independently for each neuron, maintaining an asynchronous population. Non-phasic cells use gL = 0. To test pulse response, Ire, was set to a defined pulse input for 1s at four time points spaced 100s apart. The pulse response was measured as the mean population spike rate response over the four pulses. (A) Mean population rate with a varied base input rate (range 100–1000). The population response in the phasic cells, shows a much more linear relation to the input, once input is sufficient to trigger phasic firing, particularly in the physiological spiking range of 1–8Hz. (B) Population spike activity in non-phasic and phasic cells with matched 500Hz base input rate and 1000Hz pulse input. The summed asynchronous bursting activity in the phasic cells does not show the bursting, but does show more variable activity and a lower mean spike rate. Each input pulse produces a distinct increase in firing rate. (C) Testing response with a varied base input rate (range 100–1000) and fixed 1000Hz pulse input. As background input increases, the mean pulse response in the non-phasic cells gradually falls, whereas in the non-phasic cells it is much more consistent. (D) Testing response with varied pulse input rate (range 100–1000Hz) and base rate set to give matched mean firing rate = 5 spikes/s (non-phasic base Ire = 255, phasic base Ire = 560). The phasic population response shows a much more linear relation to the input pulse rate.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475655&req=5

pcbi-1002740-g009: Comparing the population spike response of phasic and non-phasic model cells.Data here is from a population of 100 identical model cells (using the fit to cell v1) run in parallel, taking as output the summed spike rate. Synaptic input uses a common rate parameter, Ire, but was generated independently for each neuron, maintaining an asynchronous population. Non-phasic cells use gL = 0. To test pulse response, Ire, was set to a defined pulse input for 1s at four time points spaced 100s apart. The pulse response was measured as the mean population spike rate response over the four pulses. (A) Mean population rate with a varied base input rate (range 100–1000). The population response in the phasic cells, shows a much more linear relation to the input, once input is sufficient to trigger phasic firing, particularly in the physiological spiking range of 1–8Hz. (B) Population spike activity in non-phasic and phasic cells with matched 500Hz base input rate and 1000Hz pulse input. The summed asynchronous bursting activity in the phasic cells does not show the bursting, but does show more variable activity and a lower mean spike rate. Each input pulse produces a distinct increase in firing rate. (C) Testing response with a varied base input rate (range 100–1000) and fixed 1000Hz pulse input. As background input increases, the mean pulse response in the non-phasic cells gradually falls, whereas in the non-phasic cells it is much more consistent. (D) Testing response with varied pulse input rate (range 100–1000Hz) and base rate set to give matched mean firing rate = 5 spikes/s (non-phasic base Ire = 255, phasic base Ire = 560). The phasic population response shows a much more linear relation to the input pulse rate.
Mentions: To study population response, we compare the summed activity of 100 model cells in two conditions: one where all cells were made phasic by setting gL = 8.5, and one where the cells were made non-phasic by setting gL = 0, but with no other change (Figure 9). To maintain an asynchronous population, we use independently generated input PSPs for each model cell, using a common input rate, parameter Ire.

Bottom Line: By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input.Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response.These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.

View Article: PubMed Central - PubMed

Affiliation: Centre for Integrative Physiology, University of Edinburgh, Edinburgh, United Kingdom.

ABSTRACT
Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing.

Show MeSH
Related in: MedlinePlus