Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit

Bezaire, Marianne; Raikov, Ivan; Burk, Kelly; Vyas, Dhrumil

doi:10.7554/elife.18566

Cited by 208 publications

(287 citation statements)

References 156 publications

(277 reference statements)

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“…Synapses play a crucial role in neural computation. Constraining large‐scale biologically realistic simulations of brain circuits require detailed estimations of quantitative synaptic electrophysiology parameters (Bezaire, Raikov, Burk, Vyas, & Soltesz, ; Markram et al, ). Brain‐wide catalogs of synaptic information may allow for data mining and systematic hypothesis testing.…”

Section: Discussionmentioning

confidence: 99%

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A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation

Moradi

Ascoli

2019

Hippocampus

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The cellular and synaptic architecture of the rodent hippocampus has been described in thousands of peer‐reviewed publications. However, no human‐ or machine‐readable public catalog of synaptic electrophysiology data exists for this or any other neural system. Harnessing state‐of‐the‐art information technology, we have developed a cloud‐based toolset for identifying empirical evidence from the scientific literature pertaining to synaptic electrophysiology, for extracting the experimental data of interest, and for linking each entry to relevant text or figure excerpts. Mining more than 1,200 published journal articles, we have identified eight different signal modalities quantified by 90 different methods to measure synaptic amplitude, kinetics, and plasticity in hippocampal neurons. We have designed a data structure that both reflects the differences and maintains the existing relations among experimental modalities. Moreover, we mapped every annotated experiment to identified potential connections, that is, specific pairs of presynaptic and postsynaptic neuron types. To this aim, we leveraged http://hippocampome.org, an open‐access knowledge base of morphologically, electrophysiologically, and molecularly characterized neuron types in the rodent hippocampal formation. Specifically, we have implemented a computational pipeline to systematically translate neuron type properties into formal queries in order to find all compatible potential connections. With this system, we have collected nearly 40,000 synaptic data entities covering 88% of the 3,120 potential connections in http://hippocampome.org. Correcting membrane potentials with respect to liquid junction potentials significantly reduced the difference between theoretical and experimental reversal potentials, thereby enabling the accurate conversion of all synaptic amplitudes to conductance. This data set allows for large‐scale hypothesis testing of the general rules governing synaptic signals. To illustrate these applications, we confirmed several expected correlations between synaptic measurements and their covariates while suggesting previously unreported ones. We release all data open‐source at http://hippocampome.org in order to further research across disciplines.

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Section: Discussionmentioning

confidence: 99%

“…Both the linear dependence and the effect size are more demarcated at physiological temperature than at room temperature. (Bezaire, Raikov, Burk, Vyas, & Soltesz, 2016;Markram et al, 2015).…”

Section: Splitting the Signals By Decay Time Constant Median Accordinmentioning

confidence: 99%

A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation

Moradi

Ascoli

2019

Hippocampus

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“…There are also interneuronal subtypes that seem to participate in both. The functional impact of such synaptic and cellular‐level model simplifications will need to be investigated in future studies using large‐scale, biologically highly realistic, complex models (Bezaire, Raikov, Burk, Vyas, & Soltesz, ).…”

Section: Discussionmentioning

confidence: 99%

Regulation of gamma‐frequency oscillation by feedforward inhibition: A computational modeling study

2019

Self Cite

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Throughout the brain, reciprocally connected excitatory and inhibitory neurons interact to produce gamma‐frequency oscillations. The emergent gamma rhythm synchronizes local neural activity and helps to select which cells should fire in each cycle. We previously found that such excitation‐inhibition microcircuits, however, have a potentially significant caveat: the frequency of the gamma oscillation and the level of selection (i.e., the percentage of cells that are allowed to fire) vary with the magnitude of the input signal. In networks with varying levels of brain activity, such a feature may produce undesirable instability on the time and spatial structure of the neural signal with a potential for adversely impacting important neural processing mechanisms. Here we propose that feedforward inhibition solves the latter instability problem of the excitation‐inhibition microcircuit. Using computer simulations, we show that the feedforward inhibitory signal reduces the dependence of both the frequency of population oscillation and the level of selection on the magnitude of the input excitation. Such a mechanism can produce stable gamma oscillations with its frequency determined only by the properties of the feedforward network, as observed in the hippocampus. As feedforward and feedback inhibition motifs commonly appear together in the brain, we hypothesize that their interaction underlies a robust implementation of general computational principles of neural processing involved in several cognitive tasks, including the formation of cell assemblies and the routing of information between brain areas.

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“…Similar to models of gamma oscillations, hippocampal theta oscillations are thought to arise primarily from synaptic interactions of GABAergic interneurons with excitatory cells [80][81][82][83]. Since not only synaptic and circuit properties of individual neurons, but also intrinsic resonant properties can contribute to hippocampal network activity, the two types of hippocampal models of network activity are not mutually exclusive.…”

Section: Frequency Specific Hippocampal Interneuronsmentioning

confidence: 99%

“…Our data on intrinsic oscillatory properties of neurochemically identified GABAergic interneurons will be of critical importance in computational models of hippocampal gamma and theta oscillations. It is reasonable to expect that intrinsic theta and gamma oscillations of GABAergic interneurons in the hippocampus are key factors in network theta and gamma activity if these data are incorporated into existing computational models of the CA1 region, such as an innovative full-scale computational model based on experimental results on intrinsic, synaptic, and circuit properties of neurochemically identified neurons [80]. The critical role of intrinsic subthreshold oscillations in network gamma oscillations has been shown in the olfactory bulb using computational and experimental approaches [72,84].…”

Section: Frequency Specific Hippocampal Interneuronsmentioning

confidence: 99%

The Critical Role of Intrinsic Membrane Oscillations

Lee¹,

Urbano²,

García‐Rill³

2018

Neurosignals

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Intrinsic, rhythmic subthreshold oscillations have been described in neurons of regions throughout the brain and have been found to influence the timing of action potentials induced by synaptic inputs. Some oscillations are sodium channel-dependent while others are calcium channel-dependent. These oscillations allow neurons to fire coherently at preferred frequencies and represent the main mechanism for maintaining high frequency network activity, especially in the cortex. Because cortical circuits are incapable of maintaining high frequency activity in the gamma range for prolonged periods, those processes dependent on continuous gamma band activity are subserved by subthreshold oscillations. As such, intrinsic oscillations, coupled with synaptic circuits, are essential to prolonged maintenance of such functions as sensory perception and “binding”, problem solving, memory, waking, and rapid eye movement (REM) sleep.

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Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit

Cited by 208 publications

References 156 publications

A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation

A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation

Regulation of gamma‐frequency oscillation by feedforward inhibition: A computational modeling study

The Critical Role of Intrinsic Membrane Oscillations

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