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Hippocampal CA1 Ripples as Inhibitory Transients.

Malerba P, Krishnan GP, Fellous JM, Bazhenov M - PLoS Comput. Biol. (2016)

Bottom Line: Memories are stored and consolidated as a result of a dialogue between the hippocampus and cortex during sleep.We found that noise-induced loss of synchrony among CA1 interneurons dynamically constrains individual ripple duration.Our study proposes a novel mechanism of hippocampal ripple generation consistent with a broad range of experimental data, and highlights the role of noise in regulating the duration of input-driven oscillatory spiking in an inhibitory network.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, California, United States of America.

ABSTRACT
Memories are stored and consolidated as a result of a dialogue between the hippocampus and cortex during sleep. Neurons active during behavior reactivate in both structures during sleep, in conjunction with characteristic brain oscillations that may form the neural substrate of memory consolidation. In the hippocampus, replay occurs within sharp wave-ripples: short bouts of high-frequency activity in area CA1 caused by excitatory activation from area CA3. In this work, we develop a computational model of ripple generation, motivated by in vivo rat data showing that ripples have a broad frequency distribution, exponential inter-arrival times and yet highly non-variable durations. Our study predicts that ripples are not persistent oscillations but result from a transient network behavior, induced by input from CA3, in which the high frequency synchronous firing of perisomatic interneurons does not depend on the time scale of synaptic inhibition. We found that noise-induced loss of synchrony among CA1 interneurons dynamically constrains individual ripple duration. Our study proposes a novel mechanism of hippocampal ripple generation consistent with a broad range of experimental data, and highlights the role of noise in regulating the duration of input-driven oscillatory spiking in an inhibitory network.

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Properties of ripples in the model.Histograms of ripple frequency (a), durations (b), number of spikes of each pyramidal cell during ripples (c) and percent of pyramidal cells spiking in a ripple (d). (e) Average cross-correlations between firing probability of interneurons (red) or pyramidal cells (black) and the band-passed LFP.
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pcbi.1004880.g003: Properties of ripples in the model.Histograms of ripple frequency (a), durations (b), number of spikes of each pyramidal cell during ripples (c) and percent of pyramidal cells spiking in a ripple (d). (e) Average cross-correlations between firing probability of interneurons (red) or pyramidal cells (black) and the band-passed LFP.

Mentions: Ripples produced by our computational model have properties consistent with the ones recorded in vivo. Fig 3 shows that the mean frequency for a given input intensity is 162.4 ± 12.5 Hz (Fig 3A), and ripple duration is 57.2 ± 3.1 ms (Fig 3B). Also, most pyramidal cells do not spike during a ripple, in fact on average a ripple shows spikes from 14.76% of the pyramidal cell population (Fig 3D), and those that do will not spike across the ripple duration, but only once (Fig 3C) in agreement with previous experimental observations [42]. Furthermore, the spiking activity of pyramidal cells is known to precede the spiking of interneurons within each ripple wave [43]. We tested this property in our model by computing the cross-correlation between the filtered LFP and the firing probability of each cell population, averaged across 40 ripples. Fig 3E shows that peaks in the correlation between pyramidal cell spiking and LFP preceded those for interneuron activity across ripple waves. For completeness, we also verified that there was no inherent rhythmic activity in the network background state that could be inducing this relationship within ripples beyond the mechanistic phenomena we report (S3 Fig). This model is consistent with CA1 activity during non-REM sleep in vivo, when ongoing theta-gamma activity is not present in the background.


Hippocampal CA1 Ripples as Inhibitory Transients.

Malerba P, Krishnan GP, Fellous JM, Bazhenov M - PLoS Comput. Biol. (2016)

Properties of ripples in the model.Histograms of ripple frequency (a), durations (b), number of spikes of each pyramidal cell during ripples (c) and percent of pyramidal cells spiking in a ripple (d). (e) Average cross-correlations between firing probability of interneurons (red) or pyramidal cells (black) and the band-passed LFP.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
getmorefigures.php?uid=PMC4836732&req=5

pcbi.1004880.g003: Properties of ripples in the model.Histograms of ripple frequency (a), durations (b), number of spikes of each pyramidal cell during ripples (c) and percent of pyramidal cells spiking in a ripple (d). (e) Average cross-correlations between firing probability of interneurons (red) or pyramidal cells (black) and the band-passed LFP.
Mentions: Ripples produced by our computational model have properties consistent with the ones recorded in vivo. Fig 3 shows that the mean frequency for a given input intensity is 162.4 ± 12.5 Hz (Fig 3A), and ripple duration is 57.2 ± 3.1 ms (Fig 3B). Also, most pyramidal cells do not spike during a ripple, in fact on average a ripple shows spikes from 14.76% of the pyramidal cell population (Fig 3D), and those that do will not spike across the ripple duration, but only once (Fig 3C) in agreement with previous experimental observations [42]. Furthermore, the spiking activity of pyramidal cells is known to precede the spiking of interneurons within each ripple wave [43]. We tested this property in our model by computing the cross-correlation between the filtered LFP and the firing probability of each cell population, averaged across 40 ripples. Fig 3E shows that peaks in the correlation between pyramidal cell spiking and LFP preceded those for interneuron activity across ripple waves. For completeness, we also verified that there was no inherent rhythmic activity in the network background state that could be inducing this relationship within ripples beyond the mechanistic phenomena we report (S3 Fig). This model is consistent with CA1 activity during non-REM sleep in vivo, when ongoing theta-gamma activity is not present in the background.

Bottom Line: Memories are stored and consolidated as a result of a dialogue between the hippocampus and cortex during sleep.We found that noise-induced loss of synchrony among CA1 interneurons dynamically constrains individual ripple duration.Our study proposes a novel mechanism of hippocampal ripple generation consistent with a broad range of experimental data, and highlights the role of noise in regulating the duration of input-driven oscillatory spiking in an inhibitory network.

View Article: PubMed Central - PubMed

Affiliation: Department of Cell Biology and Neuroscience, University of California Riverside, Riverside, California, United States of America.

ABSTRACT
Memories are stored and consolidated as a result of a dialogue between the hippocampus and cortex during sleep. Neurons active during behavior reactivate in both structures during sleep, in conjunction with characteristic brain oscillations that may form the neural substrate of memory consolidation. In the hippocampus, replay occurs within sharp wave-ripples: short bouts of high-frequency activity in area CA1 caused by excitatory activation from area CA3. In this work, we develop a computational model of ripple generation, motivated by in vivo rat data showing that ripples have a broad frequency distribution, exponential inter-arrival times and yet highly non-variable durations. Our study predicts that ripples are not persistent oscillations but result from a transient network behavior, induced by input from CA3, in which the high frequency synchronous firing of perisomatic interneurons does not depend on the time scale of synaptic inhibition. We found that noise-induced loss of synchrony among CA1 interneurons dynamically constrains individual ripple duration. Our study proposes a novel mechanism of hippocampal ripple generation consistent with a broad range of experimental data, and highlights the role of noise in regulating the duration of input-driven oscillatory spiking in an inhibitory network.

Show MeSH