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Network Mechanisms Generating Abnormal and Normal Hippocampal High-Frequency Oscillations: A Computational Analysis.
Christian G Fink1, Stephen Gliske2, Nicholas Catoni3
1Department of Physics & Astronomy and Neuroscience Program, Ohio Wesleyan University, Delaware, OH, USA.
Eneuro
|July 7, 2015
Summary
High-frequency oscillations (HFOs) in epilepsy research are difficult to distinguish. Computational models reveal that network input, not just frequency, determines HFOs, unifying normal and pathological ripple mechanisms.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Epilepsy Research
Background:
- High-frequency oscillations (HFOs) are potential epilepsy biomarkers, classified as ripples (100-250 Hz) or fast ripples (>250 Hz).
- Distinguishing normal from pathological HFOs, particularly fast ripples in the hippocampus, remains challenging.
- Existing research suggests fast ripples are more specific to epileptic tissue, but mechanisms are not fully understood.
Purpose of the Study:
- To investigate network mechanisms underlying normal ripples, pathological ripples, and fast ripples using a computational hippocampus model.
- To unify prior findings on HFO generation mechanisms.
- To predict novel mechanisms for abnormal HFOs.
Main Methods:
- Development and utilization of a computational model of the hippocampus.
- Simulation of network activity to generate and analyze different types of HFOs.
- Investigation of the impact of varying connectivity and network input on HFO characteristics.
Main Results:
- HFOs are emergent phenomena influenced by network connectivity and input.
- Both normal and abnormal HFOs can produce similar ripple frequencies, making peak frequency an unreliable differentiator.
- Abnormal ripples result from excessive input to pyramidal cells, overpowering network inhibition and causing uncoordinated firing.
- Fast ripples arise sporadically under the specific conditions that generate abnormal ripples.
- Coherent HFOs, including abnormal ripples and fast ripples, can occur even with asynchronous network activity.
Conclusions:
- Peak frequency alone cannot distinguish normal from pathological HFOs.
- Abnormal HFOs are generic phenomena driven by network inhibition/excitation balance and input.
- A unifying network-based explanation links pathological ripples and fast ripples.
- The study provides a comprehensive model for understanding the spectrum of HFOs from normal to pathological states.
