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Event timing in associative learning: from biochemical reaction dynamics to behavioural observations.

Yarali A, Nehrkorn J, Tanimoto H, Herz AV - PLoS ONE (2012)

Bottom Line: During training, an odour-induced Ca(++) signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca(++)-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour.Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning.We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute of Neurobiology, Martinsried, Germany. yarali@neuro.mpg.de

ABSTRACT
Associative learning relies on event timing. Fruit flies for example, once trained with an odour that precedes electric shock, subsequently avoid this odour (punishment learning); if, on the other hand the odour follows the shock during training, it is approached later on (relief learning). During training, an odour-induced Ca(++) signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca(++)-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour. In Aplysia, the effect of serotonin on the corresponding adenylate cyclase is bi-directionally modulated by Ca(++), depending on the relative timing of the two inputs. Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning. We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems.

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Influence of the transmitter duration.With a fixed Ca++ input, three different transmitter inputs are tested (top). They are all initiated at 210 s, rise to a peak of 7·104 molecules/µm2 within 40 ms after the onset, but decay with different time constants as indicated above the panels. We plot the resulting adenylate cyclase dynamics (middle) and the ISI-dependent associative effects (bottom). In terms of the percent sizes of associative effects, changing the transmitter decay time constant from 0.1 to 1 (the first two cases) hardly makes a difference. A slower decaying transmitter input (the last case) broadens the dynamics of adenylate cyclase activation/deactivation, resulting in much higher cAMP production in the control condition; thus, the percent associative effects remain small. As for the ISI-dependence of the associative effects, short transmitter inputs (the first two cases) give good fits to the situation in Fig. 1; when a slower decaying transmitter input is used (the last case), the positive associative effect only occurs for large positive ISIs, due to the broadened adenylate cyclase activation/deactivation dynamics.
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pone-0032885-g007: Influence of the transmitter duration.With a fixed Ca++ input, three different transmitter inputs are tested (top). They are all initiated at 210 s, rise to a peak of 7·104 molecules/µm2 within 40 ms after the onset, but decay with different time constants as indicated above the panels. We plot the resulting adenylate cyclase dynamics (middle) and the ISI-dependent associative effects (bottom). In terms of the percent sizes of associative effects, changing the transmitter decay time constant from 0.1 to 1 (the first two cases) hardly makes a difference. A slower decaying transmitter input (the last case) broadens the dynamics of adenylate cyclase activation/deactivation, resulting in much higher cAMP production in the control condition; thus, the percent associative effects remain small. As for the ISI-dependence of the associative effects, short transmitter inputs (the first two cases) give good fits to the situation in Fig. 1; when a slower decaying transmitter input is used (the last case), the positive associative effect only occurs for large positive ISIs, due to the broadened adenylate cyclase activation/deactivation dynamics.

Mentions: We first study the effect of changes in the duration of the transmitter (Fig. 7), keeping the Ca++ input the same as in the previous experiments. For a fixed rise time of the transmitter, increasing its decay time constant from 0.1 s to 1 s hardly changes the size of the associative effects (Fig. 7, the first two cases). A more slowly decaying transmitter input on the other hand, due to a much higher control level of cAMP production, allows only for smaller percent associative effects (Fig. 7, the last case). A corresponding effect of shock duration on the strength of learning remains to be probed for in fly learning experiments. As for the ISI-dependence of the associative effects, short transmitter inputs give good fit to the behavioural situation in Fig. 1 (Fig. 7, the first two cases). For more slowly decaying transmitter inputs, the positive associative effect only occurs for longer ISIs due to the broadened dynamics of adenylate cyclase activation/deactivation (Fig. 7, the last case). Quantitatively, we cannot provide a detailed comparison between these effects and those found at the behavioural level, since the dynamics of dopamine availability in the synaptic cleft upon shock stimulation is not known. It is however noteworthy that also in Drosophila behavioural experiments shock duration affects the window of ISIs appropriate for relief learning. For example, in Fig. 1, the shock lasts for 15 s; accordingly, relief learning is possible with ISIs longer than 15 s. For a 1.5s-long shock stimulus, however, an ISI of 2 s already supports relief learning (Fig. 8C of [17]). This invites a more systematic behavioural analysis of the effect of shock duration on relief learning.


Event timing in associative learning: from biochemical reaction dynamics to behavioural observations.

Yarali A, Nehrkorn J, Tanimoto H, Herz AV - PLoS ONE (2012)

Influence of the transmitter duration.With a fixed Ca++ input, three different transmitter inputs are tested (top). They are all initiated at 210 s, rise to a peak of 7·104 molecules/µm2 within 40 ms after the onset, but decay with different time constants as indicated above the panels. We plot the resulting adenylate cyclase dynamics (middle) and the ISI-dependent associative effects (bottom). In terms of the percent sizes of associative effects, changing the transmitter decay time constant from 0.1 to 1 (the first two cases) hardly makes a difference. A slower decaying transmitter input (the last case) broadens the dynamics of adenylate cyclase activation/deactivation, resulting in much higher cAMP production in the control condition; thus, the percent associative effects remain small. As for the ISI-dependence of the associative effects, short transmitter inputs (the first two cases) give good fits to the situation in Fig. 1; when a slower decaying transmitter input is used (the last case), the positive associative effect only occurs for large positive ISIs, due to the broadened adenylate cyclase activation/deactivation dynamics.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3316544&req=5

pone-0032885-g007: Influence of the transmitter duration.With a fixed Ca++ input, three different transmitter inputs are tested (top). They are all initiated at 210 s, rise to a peak of 7·104 molecules/µm2 within 40 ms after the onset, but decay with different time constants as indicated above the panels. We plot the resulting adenylate cyclase dynamics (middle) and the ISI-dependent associative effects (bottom). In terms of the percent sizes of associative effects, changing the transmitter decay time constant from 0.1 to 1 (the first two cases) hardly makes a difference. A slower decaying transmitter input (the last case) broadens the dynamics of adenylate cyclase activation/deactivation, resulting in much higher cAMP production in the control condition; thus, the percent associative effects remain small. As for the ISI-dependence of the associative effects, short transmitter inputs (the first two cases) give good fits to the situation in Fig. 1; when a slower decaying transmitter input is used (the last case), the positive associative effect only occurs for large positive ISIs, due to the broadened adenylate cyclase activation/deactivation dynamics.
Mentions: We first study the effect of changes in the duration of the transmitter (Fig. 7), keeping the Ca++ input the same as in the previous experiments. For a fixed rise time of the transmitter, increasing its decay time constant from 0.1 s to 1 s hardly changes the size of the associative effects (Fig. 7, the first two cases). A more slowly decaying transmitter input on the other hand, due to a much higher control level of cAMP production, allows only for smaller percent associative effects (Fig. 7, the last case). A corresponding effect of shock duration on the strength of learning remains to be probed for in fly learning experiments. As for the ISI-dependence of the associative effects, short transmitter inputs give good fit to the behavioural situation in Fig. 1 (Fig. 7, the first two cases). For more slowly decaying transmitter inputs, the positive associative effect only occurs for longer ISIs due to the broadened dynamics of adenylate cyclase activation/deactivation (Fig. 7, the last case). Quantitatively, we cannot provide a detailed comparison between these effects and those found at the behavioural level, since the dynamics of dopamine availability in the synaptic cleft upon shock stimulation is not known. It is however noteworthy that also in Drosophila behavioural experiments shock duration affects the window of ISIs appropriate for relief learning. For example, in Fig. 1, the shock lasts for 15 s; accordingly, relief learning is possible with ISIs longer than 15 s. For a 1.5s-long shock stimulus, however, an ISI of 2 s already supports relief learning (Fig. 8C of [17]). This invites a more systematic behavioural analysis of the effect of shock duration on relief learning.

Bottom Line: During training, an odour-induced Ca(++) signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca(++)-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour.Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning.We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute of Neurobiology, Martinsried, Germany. yarali@neuro.mpg.de

ABSTRACT
Associative learning relies on event timing. Fruit flies for example, once trained with an odour that precedes electric shock, subsequently avoid this odour (punishment learning); if, on the other hand the odour follows the shock during training, it is approached later on (relief learning). During training, an odour-induced Ca(++) signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca(++)-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour. In Aplysia, the effect of serotonin on the corresponding adenylate cyclase is bi-directionally modulated by Ca(++), depending on the relative timing of the two inputs. Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning. We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems.

Show MeSH
Related in: MedlinePlus