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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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Selective input from CA3 induces sequential activation of CA1 pyramidal cells in model.(a i) Top panel, the CA3 input currents delivered to selected cells (sequence cells) during a ripple. Bottom panel, simultaneous rastergram of sequence cells. (a ii) Distribution of the input drives to all pyramidal cells in the model. In red, the values for sequence cells. (a iii) Average spike time differences for all sequence cells: each line is the average spike time difference between a given cell and all cells in the sequence, averaged across 40 ripples. The lines cross zero when the spike time difference with itself is reported. Note that in this case sequential spiking behavior during ripples is not present. (a iv) Plot of each pyramidal cell vs the fraction of ripples it visited. In black all cells, circled in red are the sequence cells. For every cell, the number of ripples in which it spiked (ripple visited) can be found and divided by the total number of ripples in the simulation. (b) Same plots as in a, but in this case selected cells only receive selective CA3 input (b i), without enhanced intrinsic excitability provided by constant direct current (see b ii). Note that in this case, the orderliness of spiking across ripples is overall preserved (see b iii). Note that most cells spike in less than 20% of the ripples, while selected “sequence” cells all visit about 70% of the ripples (see b iv). (c) Same as a, but in this case selected cells receive both enhanced intrinsic excitability (see c ii) and selective temporal ordering in CA3 input (see c i). The orderliness of the average spike time difference curves emphasizes that cells spike in order across multiple ripples (see c iii), and sequence cells spike in more ripples than all other cells (see c iv).
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pcbi.1004880.g008: Selective input from CA3 induces sequential activation of CA1 pyramidal cells in model.(a i) Top panel, the CA3 input currents delivered to selected cells (sequence cells) during a ripple. Bottom panel, simultaneous rastergram of sequence cells. (a ii) Distribution of the input drives to all pyramidal cells in the model. In red, the values for sequence cells. (a iii) Average spike time differences for all sequence cells: each line is the average spike time difference between a given cell and all cells in the sequence, averaged across 40 ripples. The lines cross zero when the spike time difference with itself is reported. Note that in this case sequential spiking behavior during ripples is not present. (a iv) Plot of each pyramidal cell vs the fraction of ripples it visited. In black all cells, circled in red are the sequence cells. For every cell, the number of ripples in which it spiked (ripple visited) can be found and divided by the total number of ripples in the simulation. (b) Same plots as in a, but in this case selected cells only receive selective CA3 input (b i), without enhanced intrinsic excitability provided by constant direct current (see b ii). Note that in this case, the orderliness of spiking across ripples is overall preserved (see b iii). Note that most cells spike in less than 20% of the ripples, while selected “sequence” cells all visit about 70% of the ripples (see b iv). (c) Same as a, but in this case selected cells receive both enhanced intrinsic excitability (see c ii) and selective temporal ordering in CA3 input (see c i). The orderliness of the average spike time difference curves emphasizes that cells spike in order across multiple ripples (see c iii), and sequence cells spike in more ripples than all other cells (see c iv).

Mentions: Hence we have two possible mechanisms with the potential of inducing reactivation: intrinsic CA1 excitability is a parameter of CA1 properties that could induce sequence reactivation, while CA3 selective input is a potential input-dependent mechanism for sequence replay in CA1. To test these two properties, we randomly selected 10 pyramidal cells (“sequence” cells) to represent neurons that reactivate sequentially during ripples. First, we increased the constant current input that the 10 selected neurons received (Fig 8A), which resulted in the appearance of a small peak at high values in the distribution of excitability of all pyramidal cells of the CA1 network (Fig 8A ii). This was introduced as a mechanism to increase the likelihood of selected cells to spike during ripples. In a second case, we changed the time course of incoming current input, only for the selected sequence cells (Fig 8B). As shown in Fig 8B–8I, each sequence cell received an input that had a peak in a narrow time window within the duration of a ripple. This peak represented the spiking of the sub-set of CA3 pyramidal neurons that were preferentially connected to the target CA1 cell; thus we assumed that there are CA3 neurons that would spike during a sequence-specific time window of the sharp wave event. In other words, in this case our model assumes that during a sharp wave-ripple there is an organized reactivation in CA3, inducing selective inputs to CA1, which results in sequential spike reactivation in CA1. Finally, in a third case, we combined both manipulations on our selected cells: increased excitability and selective CA3 inputs. For each case, we show whether the inputs from CA3 are selective in panel i, and whether sequence cells received extra excitability in panel ii.


Hippocampal CA1 Ripples as Inhibitory Transients.

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

Selective input from CA3 induces sequential activation of CA1 pyramidal cells in model.(a i) Top panel, the CA3 input currents delivered to selected cells (sequence cells) during a ripple. Bottom panel, simultaneous rastergram of sequence cells. (a ii) Distribution of the input drives to all pyramidal cells in the model. In red, the values for sequence cells. (a iii) Average spike time differences for all sequence cells: each line is the average spike time difference between a given cell and all cells in the sequence, averaged across 40 ripples. The lines cross zero when the spike time difference with itself is reported. Note that in this case sequential spiking behavior during ripples is not present. (a iv) Plot of each pyramidal cell vs the fraction of ripples it visited. In black all cells, circled in red are the sequence cells. For every cell, the number of ripples in which it spiked (ripple visited) can be found and divided by the total number of ripples in the simulation. (b) Same plots as in a, but in this case selected cells only receive selective CA3 input (b i), without enhanced intrinsic excitability provided by constant direct current (see b ii). Note that in this case, the orderliness of spiking across ripples is overall preserved (see b iii). Note that most cells spike in less than 20% of the ripples, while selected “sequence” cells all visit about 70% of the ripples (see b iv). (c) Same as a, but in this case selected cells receive both enhanced intrinsic excitability (see c ii) and selective temporal ordering in CA3 input (see c i). The orderliness of the average spike time difference curves emphasizes that cells spike in order across multiple ripples (see c iii), and sequence cells spike in more ripples than all other cells (see c iv).
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
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pcbi.1004880.g008: Selective input from CA3 induces sequential activation of CA1 pyramidal cells in model.(a i) Top panel, the CA3 input currents delivered to selected cells (sequence cells) during a ripple. Bottom panel, simultaneous rastergram of sequence cells. (a ii) Distribution of the input drives to all pyramidal cells in the model. In red, the values for sequence cells. (a iii) Average spike time differences for all sequence cells: each line is the average spike time difference between a given cell and all cells in the sequence, averaged across 40 ripples. The lines cross zero when the spike time difference with itself is reported. Note that in this case sequential spiking behavior during ripples is not present. (a iv) Plot of each pyramidal cell vs the fraction of ripples it visited. In black all cells, circled in red are the sequence cells. For every cell, the number of ripples in which it spiked (ripple visited) can be found and divided by the total number of ripples in the simulation. (b) Same plots as in a, but in this case selected cells only receive selective CA3 input (b i), without enhanced intrinsic excitability provided by constant direct current (see b ii). Note that in this case, the orderliness of spiking across ripples is overall preserved (see b iii). Note that most cells spike in less than 20% of the ripples, while selected “sequence” cells all visit about 70% of the ripples (see b iv). (c) Same as a, but in this case selected cells receive both enhanced intrinsic excitability (see c ii) and selective temporal ordering in CA3 input (see c i). The orderliness of the average spike time difference curves emphasizes that cells spike in order across multiple ripples (see c iii), and sequence cells spike in more ripples than all other cells (see c iv).
Mentions: Hence we have two possible mechanisms with the potential of inducing reactivation: intrinsic CA1 excitability is a parameter of CA1 properties that could induce sequence reactivation, while CA3 selective input is a potential input-dependent mechanism for sequence replay in CA1. To test these two properties, we randomly selected 10 pyramidal cells (“sequence” cells) to represent neurons that reactivate sequentially during ripples. First, we increased the constant current input that the 10 selected neurons received (Fig 8A), which resulted in the appearance of a small peak at high values in the distribution of excitability of all pyramidal cells of the CA1 network (Fig 8A ii). This was introduced as a mechanism to increase the likelihood of selected cells to spike during ripples. In a second case, we changed the time course of incoming current input, only for the selected sequence cells (Fig 8B). As shown in Fig 8B–8I, each sequence cell received an input that had a peak in a narrow time window within the duration of a ripple. This peak represented the spiking of the sub-set of CA3 pyramidal neurons that were preferentially connected to the target CA1 cell; thus we assumed that there are CA3 neurons that would spike during a sequence-specific time window of the sharp wave event. In other words, in this case our model assumes that during a sharp wave-ripple there is an organized reactivation in CA3, inducing selective inputs to CA1, which results in sequential spike reactivation in CA1. Finally, in a third case, we combined both manipulations on our selected cells: increased excitability and selective CA3 inputs. For each case, we show whether the inputs from CA3 are selective in panel i, and whether sequence cells received extra excitability in panel ii.

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
Related in: MedlinePlus