Computational analysis of network activity and spatial reach of sharp wave-ripples

PLOS ONE, Nov 2019

Network oscillations of different frequencies, durations and amplitudes are hypothesized to coordinate information processing and transfer across brain areas. Among these oscillations, hippocampal sharp wave-ripple complexes (SPW-Rs) are one of the most prominent. SPW-Rs occurring in the hippocampus are suggested to play essential roles in memory consolidation as well as information transfer to the neocortex. To-date, most of the knowledge about SPW-Rs comes from experimental studies averaging responses from neuronal populations monitored by conventional microelectrodes. In this work, we investigate spatiotemporal characteristics of SPW-Rs and how microelectrode size and distance influence SPW-R recordings using a biophysical model of hippocampus. We also explore contributions from neuronal spikes and synaptic potentials to SPW-Rs based on two different types of network activity. Our study suggests that neuronal spikes from pyramidal cells contribute significantly to ripples while high amplitude sharp waves mainly arise from synaptic activity. Our simulations on spatial reach of SPW-Rs show that the amplitudes of sharp waves and ripples exhibit a steep decrease with distance from the network and this effect is more prominent for smaller area electrodes. Furthermore, the amplitude of the signal decreases strongly with increasing electrode surface area as a result of averaging. The relative decrease is more pronounced when the recording electrode is closer to the source of the activity. Through simulations of field potentials across a high-density microelectrode array, we demonstrate the importance of finding the ideal spatial resolution for capturing SPW-Rs with great sensitivity. Our work provides insights on contributions from spikes and synaptic potentials to SPW-Rs and describes the effect of measurement configuration on LFPs to guide experimental studies towards improved SPW-R recordings.

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Computational analysis of network activity and spatial reach of sharp wave-ripples

Kuzum D (2017) Computational analysis of network activity and spatial reach of sharp wave-ripples. PLoS ONE 12(9): e0184542. https://doi.org/ 10.1371/journal.pone.0184542 Computational analysis of network activity and spatial reach of sharp wave-ripples Sadullah Canakci 0 1 2 Muhammed Faruk Toy 0 2 Ahmet Fatih Inci 0 2 Xin Liu 0 2 Duygu Kuzum 0 2 ☯ These authors contributed equally to this work. 0 2 0 2 0 Funding: We would like to acknowledge Office of Naval Research Young Investigator Award and UC San Diego Frontiers of Innovation Scholars Program for funding this research. We also 1 Electrical and Computer Engineering Department, Boston University , Boston , Massachusetts, United States of America, 2 Electrical and Computer Engineering Department, University of California San Diego, La Jolla, California, United States of America, 3 Electrical and Electronics Engineering, Middle East Technical University , Ankara , Turkey , 4 Faculty of Engineering and Natural Sciences, Sabanci University , Istanbul , Turkey 2 Editor: Liset Menendez de la Prida , Consejo Superior de Investigaciones Cientificas , SPAIN Network oscillations of different frequencies, durations and amplitudes are hypothesized to coordinate information processing and transfer across brain areas. Among these oscillations, hippocampal sharp wave-ripple complexes (SPW-Rs) are one of the most prominent. SPW-Rs occurring in the hippocampus are suggested to play essential roles in memory consolidation as well as information transfer to the neocortex. To-date, most of the knowledge about SPW-Rs comes from experimental studies averaging responses from neuronal populations monitored by conventional microelectrodes. In this work, we investigate spatiotemporal characteristics of SPW-Rs and how microelectrode size and distance influence SPWR recordings using a biophysical model of hippocampus. We also explore contributions from neuronal spikes and synaptic potentials to SPW-Rs based on two different types of network activity. Our study suggests that neuronal spikes from pyramidal cells contribute significantly to ripples while high amplitude sharp waves mainly arise from synaptic activity. Our simulations on spatial reach of SPW-Rs show that the amplitudes of sharp waves and ripples exhibit a steep decrease with distance from the network and this effect is more prominent for smaller area electrodes. Furthermore, the amplitude of the signal decreases strongly with increasing electrode surface area as a result of averaging. The relative decrease is more pronounced when the recording electrode is closer to the source of the activity. Through simulations of field potentials across a high-density microelectrode array, we demonstrate the importance of finding the ideal spatial resolution for capturing SPW-Rs with great sensitivity. Our work provides insights on contributions from spikes and synaptic potentials to SPWRs and describes the effect of measurement configuration on LFPs to guide experimental studies towards improved SPW-R recordings. - acknowledge UCSD Center for Multiscale Imaging of Brain Function for research support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Introduction Hippocampal network oscillations have been extensively investigated due to their potential roles in learning, memory, spatial navigation, and consolidation of memories [1±5]. The anatomically well-defined structure of the hippocampus has enabled numerous neuroscience studies over decades. Three major network oscillations generated in hippocampus, theta (6±10 Hz), gamma (30±120), and SPW-Rs (150±250 Hz), are hypothesized to participate in memory formation and consolidation [ 2 ]. Among these, SPW-Rs are the most synchronous pattern in the mammalian brain [ 2 ]. They occur in the hippocampus during slow wave sleep, immobility, and consummatory behaviors [ 6 ]. SPW-Rs are composed of high amplitude sharp waves and high frequency ripple oscillations. Recent studies have shown that during SPW-Rs, firing patterns of sequentially activated place cells, observed during wakeful exploration, are replayed in forward or reverse order [7±10]. Online disruption of SPW-Rs has been shown to cause memory impairment [ 11,12 ], indicating SPW-Rs' role in memory consolidation. SPW-R replay has also been suggested to play important roles in combining recently acquired and pre-existing information to influence decisions, plan actions, and potentially allow for creative thoughts [2]. Understanding the neural processes and physiological roles of different hippocampal regions during SPW-Rs generation is crucial towards deciphering the mechanisms for replay and memory consolidation. A model explaining SPW-R generation in the hippocampus has been proposed by Buzsaki et al. [ 13,14 ]. According to this model, SPW-Rs arise from the excitatory recurrent system of the CA3 region. The recurrent connectivity in th (...truncated)


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Sadullah Canakci, Muhammed Faruk Toy, Ahmet Fatih Inci, Xin Liu, Duygu Kuzum. Computational analysis of network activity and spatial reach of sharp wave-ripples, PLOS ONE, 2017, Volume 12, Issue 9, DOI: 10.1371/journal.pone.0184542