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Network Mechanisms Generating Abnormal and Normal Hippocampal High-Frequency Oscillations: A Computational Analysis.

Fink CG, Gliske S, Catoni N, Stacey WC - eNeuro (2015 May-Jun)

Bottom Line: Abnormal ripples are generic phenomena that arise when input to pyramidal cells overcomes network inhibition, resulting in high-frequency, uncoordinated firing.Lastly, we show that such abnormal conditions do not require any specific network structure to produce coherent HFOs, as even completely asynchronous activity is capable of producing abnormal ripples and fast ripples in this manner.These results provide a generic, network-based explanation for the link between pathological ripples and fast ripples, and a unifying description for the entire spectrum from normal ripples to pathological fast ripples.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physics & Astronomy and Neuroscience Program, Ohio Wesleyan University, Delaware, OH, USA.

ABSTRACT

High-frequency oscillations (HFOs) are an intriguing potential biomarker for epilepsy, typically categorized according to peak frequency as either ripples (100-250 Hz) or fast ripples (>250 Hz). In the hippocampus, fast ripples were originally thought to be more specific to epileptic tissue, but it is still very di cult to distinguish which HFOs are caused by normal versus pathological brain activity. In this study we use a computational model of hippocampus to investigate possible network mechanisms underpinning normal ripples, pathological ripples, and fast ripples. Our results unify several prior findings regarding HFO mechanisms, and also make several new predictions regarding abnormal HFOs. We show that HFOs are generic, emergent phenomena whose characteristics reflect a wide range of connectivity and network input. Although produced by di erent mechanisms, both normal and abnormal HFOs generate similar ripple frequencies, underscoring that peak frequency is unable to distinguish the two. Abnormal ripples are generic phenomena that arise when input to pyramidal cells overcomes network inhibition, resulting in high-frequency, uncoordinated firing. In addition, fast ripples transiently and sporadically arise from the precise conditions that produce abnormal ripples. Lastly, we show that such abnormal conditions do not require any specific network structure to produce coherent HFOs, as even completely asynchronous activity is capable of producing abnormal ripples and fast ripples in this manner. These results provide a generic, network-based explanation for the link between pathological ripples and fast ripples, and a unifying description for the entire spectrum from normal ripples to pathological fast ripples.

No MeSH data available.


Related in: MedlinePlus

Emergence of fast ripples in an uncoupled, asynchronously spiking network. Using the same parameters as the highest-frequency data in Figure 6, a 20,000 ms simulation was performed to identify the emergence of HFOs in a network of 80 uncoupled pyramidal cells driven by high levels of uncorrelated noisy input. A, LFP spectrogram of a 1000 ms interval demonstrates that both ripple (R) and fast ripple (FR) episodes emerged sporadically. B, Spike-timing histogram relative to ripple phase, averaged over all 78 observed ripple episodes. C, Spike-timing histogram relative to ripple phase, averaged over all 26 observed fast ripple episodes. Ripples occurred when the 80 cells achieved brief unimodal spike time distribution, and fast ripples occurred when the distribution was transiently bimodal. Error bars represent SEM over all observed ripple/fast ripple episodes.
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Figure 7: Emergence of fast ripples in an uncoupled, asynchronously spiking network. Using the same parameters as the highest-frequency data in Figure 6, a 20,000 ms simulation was performed to identify the emergence of HFOs in a network of 80 uncoupled pyramidal cells driven by high levels of uncorrelated noisy input. A, LFP spectrogram of a 1000 ms interval demonstrates that both ripple (R) and fast ripple (FR) episodes emerged sporadically. B, Spike-timing histogram relative to ripple phase, averaged over all 78 observed ripple episodes. C, Spike-timing histogram relative to ripple phase, averaged over all 26 observed fast ripple episodes. Ripples occurred when the 80 cells achieved brief unimodal spike time distribution, and fast ripples occurred when the distribution was transiently bimodal. Error bars represent SEM over all observed ripple/fast ripple episodes.

Mentions: Figure 6A shows that the ripple (<250 Hz) frequencies dominated despite the presence of the fast ripple harmonics. However, our observations of the raw data revealed that there were many instances in which fast ripples dominated, just as in Figure 5C,D. To investigate how such fast ripple activity emerges in this asynchronous network, we ran a long simulation (20,000 ms; Fig. 7) using the same uncoupled pyramidal cell network as used in Figure 6, with the noise intensity set to the highest level that sustained network oscillations without going into depolarization block (0.77 nA2). As shown in Figure 7A, we observed that strong ripple oscillations at ≈200 Hz (which matched the mean firing rate of individual neurons) dominated the LFP the majority of the time, but that fast ripple episodes emerged spontaneously, typically lasting 20–50 ms. Spike-time histograms relative to ripple phase indicated that the ripple episodes had a single cluster (Fig. 7B), whereas fast ripple episodes occurred due to two out-of-phase spiking clusters (Fig. 7C). This is similar to what has been proposed previously by Menendez de la Prida’s group (Foffani et al., 2007; Ibarz et al., 2010). Most striking, however, is that in our results there is no organizing mechanism for such bicluster dynamical states; they emerge briefly and spontaneously from asynchronous activity in a completely uncoupled network. Such fast ripples are therefore not a result of decreased spike timing reliability, but emerge by chance when the randomly evolving spike-time structure happens to assume a bimodal form.


Network Mechanisms Generating Abnormal and Normal Hippocampal High-Frequency Oscillations: A Computational Analysis.

Fink CG, Gliske S, Catoni N, Stacey WC - eNeuro (2015 May-Jun)

Emergence of fast ripples in an uncoupled, asynchronously spiking network. Using the same parameters as the highest-frequency data in Figure 6, a 20,000 ms simulation was performed to identify the emergence of HFOs in a network of 80 uncoupled pyramidal cells driven by high levels of uncorrelated noisy input. A, LFP spectrogram of a 1000 ms interval demonstrates that both ripple (R) and fast ripple (FR) episodes emerged sporadically. B, Spike-timing histogram relative to ripple phase, averaged over all 78 observed ripple episodes. C, Spike-timing histogram relative to ripple phase, averaged over all 26 observed fast ripple episodes. Ripples occurred when the 80 cells achieved brief unimodal spike time distribution, and fast ripples occurred when the distribution was transiently bimodal. Error bars represent SEM over all observed ripple/fast ripple episodes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4487885&req=5

Figure 7: Emergence of fast ripples in an uncoupled, asynchronously spiking network. Using the same parameters as the highest-frequency data in Figure 6, a 20,000 ms simulation was performed to identify the emergence of HFOs in a network of 80 uncoupled pyramidal cells driven by high levels of uncorrelated noisy input. A, LFP spectrogram of a 1000 ms interval demonstrates that both ripple (R) and fast ripple (FR) episodes emerged sporadically. B, Spike-timing histogram relative to ripple phase, averaged over all 78 observed ripple episodes. C, Spike-timing histogram relative to ripple phase, averaged over all 26 observed fast ripple episodes. Ripples occurred when the 80 cells achieved brief unimodal spike time distribution, and fast ripples occurred when the distribution was transiently bimodal. Error bars represent SEM over all observed ripple/fast ripple episodes.
Mentions: Figure 6A shows that the ripple (<250 Hz) frequencies dominated despite the presence of the fast ripple harmonics. However, our observations of the raw data revealed that there were many instances in which fast ripples dominated, just as in Figure 5C,D. To investigate how such fast ripple activity emerges in this asynchronous network, we ran a long simulation (20,000 ms; Fig. 7) using the same uncoupled pyramidal cell network as used in Figure 6, with the noise intensity set to the highest level that sustained network oscillations without going into depolarization block (0.77 nA2). As shown in Figure 7A, we observed that strong ripple oscillations at ≈200 Hz (which matched the mean firing rate of individual neurons) dominated the LFP the majority of the time, but that fast ripple episodes emerged spontaneously, typically lasting 20–50 ms. Spike-time histograms relative to ripple phase indicated that the ripple episodes had a single cluster (Fig. 7B), whereas fast ripple episodes occurred due to two out-of-phase spiking clusters (Fig. 7C). This is similar to what has been proposed previously by Menendez de la Prida’s group (Foffani et al., 2007; Ibarz et al., 2010). Most striking, however, is that in our results there is no organizing mechanism for such bicluster dynamical states; they emerge briefly and spontaneously from asynchronous activity in a completely uncoupled network. Such fast ripples are therefore not a result of decreased spike timing reliability, but emerge by chance when the randomly evolving spike-time structure happens to assume a bimodal form.

Bottom Line: Abnormal ripples are generic phenomena that arise when input to pyramidal cells overcomes network inhibition, resulting in high-frequency, uncoordinated firing.Lastly, we show that such abnormal conditions do not require any specific network structure to produce coherent HFOs, as even completely asynchronous activity is capable of producing abnormal ripples and fast ripples in this manner.These results provide a generic, network-based explanation for the link between pathological ripples and fast ripples, and a unifying description for the entire spectrum from normal ripples to pathological fast ripples.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Physics & Astronomy and Neuroscience Program, Ohio Wesleyan University, Delaware, OH, USA.

ABSTRACT

High-frequency oscillations (HFOs) are an intriguing potential biomarker for epilepsy, typically categorized according to peak frequency as either ripples (100-250 Hz) or fast ripples (>250 Hz). In the hippocampus, fast ripples were originally thought to be more specific to epileptic tissue, but it is still very di cult to distinguish which HFOs are caused by normal versus pathological brain activity. In this study we use a computational model of hippocampus to investigate possible network mechanisms underpinning normal ripples, pathological ripples, and fast ripples. Our results unify several prior findings regarding HFO mechanisms, and also make several new predictions regarding abnormal HFOs. We show that HFOs are generic, emergent phenomena whose characteristics reflect a wide range of connectivity and network input. Although produced by di erent mechanisms, both normal and abnormal HFOs generate similar ripple frequencies, underscoring that peak frequency is unable to distinguish the two. Abnormal ripples are generic phenomena that arise when input to pyramidal cells overcomes network inhibition, resulting in high-frequency, uncoordinated firing. In addition, fast ripples transiently and sporadically arise from the precise conditions that produce abnormal ripples. Lastly, we show that such abnormal conditions do not require any specific network structure to produce coherent HFOs, as even completely asynchronous activity is capable of producing abnormal ripples and fast ripples in this manner. These results provide a generic, network-based explanation for the link between pathological ripples and fast ripples, and a unifying description for the entire spectrum from normal ripples to pathological fast ripples.

No MeSH data available.


Related in: MedlinePlus