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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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The model's burst firing mechanism.The data here shows two typical bursts from the model fitted to cell v4. The burst mechanism is driven by the spike triggered accumulation of [Ca2+]i and dynorphin. The [Ca2+]i signal inhibits the hyperpolarising K+ leak current, increasing firing and creating a positive feedback that sustains a burst. The more slowly accumulating dynorphin signal opposes the effect of [Ca2+]i, eventually causing burst termination and driving a silent period of sustained hyperpolarisation. The positive feedback combined with the two opposing effects acting on different timescales creates an emergent bistability, shown in the rapid shifts of the K+ leak (L) activation and the resulting effect on membrane potential (VL).
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pcbi-1002740-g004: The model's burst firing mechanism.The data here shows two typical bursts from the model fitted to cell v4. The burst mechanism is driven by the spike triggered accumulation of [Ca2+]i and dynorphin. The [Ca2+]i signal inhibits the hyperpolarising K+ leak current, increasing firing and creating a positive feedback that sustains a burst. The more slowly accumulating dynorphin signal opposes the effect of [Ca2+]i, eventually causing burst termination and driving a silent period of sustained hyperpolarisation. The positive feedback combined with the two opposing effects acting on different timescales creates an emergent bistability, shown in the rapid shifts of the K+ leak (L) activation and the resulting effect on membrane potential (VL).

Mentions: The bistable burst firing mechanism is based on opposing effects of [Ca2+]i and dynorphin, acting on different timescales. These do not act deterministically, but shift the probability of a burst starting or stopping, subject to the stochastic synaptic input. When rapid successive spikes arise during a silent period, they cause an increase in [Ca2+]i which begins to suppress the hyperpolarising K+ leak current. This triggers activity-dependent positive feedback, increasing firing rate and hence [Ca2+]i. This feedback becomes self-sustaining, maintaining the suppression of the leak current and hence allowing spike activity to be sustained at a relatively stable level (Figure 4).


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

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

The model's burst firing mechanism.The data here shows two typical bursts from the model fitted to cell v4. The burst mechanism is driven by the spike triggered accumulation of [Ca2+]i and dynorphin. The [Ca2+]i signal inhibits the hyperpolarising K+ leak current, increasing firing and creating a positive feedback that sustains a burst. The more slowly accumulating dynorphin signal opposes the effect of [Ca2+]i, eventually causing burst termination and driving a silent period of sustained hyperpolarisation. The positive feedback combined with the two opposing effects acting on different timescales creates an emergent bistability, shown in the rapid shifts of the K+ leak (L) activation and the resulting effect on membrane potential (VL).
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1002740-g004: The model's burst firing mechanism.The data here shows two typical bursts from the model fitted to cell v4. The burst mechanism is driven by the spike triggered accumulation of [Ca2+]i and dynorphin. The [Ca2+]i signal inhibits the hyperpolarising K+ leak current, increasing firing and creating a positive feedback that sustains a burst. The more slowly accumulating dynorphin signal opposes the effect of [Ca2+]i, eventually causing burst termination and driving a silent period of sustained hyperpolarisation. The positive feedback combined with the two opposing effects acting on different timescales creates an emergent bistability, shown in the rapid shifts of the K+ leak (L) activation and the resulting effect on membrane potential (VL).
Mentions: The bistable burst firing mechanism is based on opposing effects of [Ca2+]i and dynorphin, acting on different timescales. These do not act deterministically, but shift the probability of a burst starting or stopping, subject to the stochastic synaptic input. When rapid successive spikes arise during a silent period, they cause an increase in [Ca2+]i which begins to suppress the hyperpolarising K+ leak current. This triggers activity-dependent positive feedback, increasing firing rate and hence [Ca2+]i. This feedback becomes self-sustaining, maintaining the suppression of the leak current and hence allowing spike activity to be sustained at a relatively stable level (Figure 4).

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