Effects of Neuromodulation on Excitatory–Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

Rich, Scott; Żochowski, Michał; Booth, Victoria

doi:10.1007/s00332-017-9438-6

Cited by 16 publications

(30 citation statements)

References 63 publications

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“…The measure used to quantify coherent activity in the simulated networks, here termed a Synchrony Measure, is a slight adaptation of a commonly used measure created by Rinzel, 1993, 1994) that quantifies the degree of spiking coincidence in the network. This particular implementation of this measure has been utilized in previous studies (Rich et al, 2016(Rich et al, , 2017(Rich et al, , 2018.…”

Section: Methodsmentioning

confidence: 99%

“…For example, the results of Hansel et al (1995) imply that an excitatory network made up of cells of the type studied here is highly unlikely to ever synchronize. Similarly, while the Pyramidal Interneuron Network Gamma (PING) mechanism is commonly cited as a mechanism causing synchronous oscillations in E-I networks (Traub et al, 1997;Ermentrout and Kopell, 1998;Whittington et al, 2000;Kopell et al, 2010), recent work has revealed that the predictions of this mechanism are altered by varying individual cellular properties and network connectivity (Rich et al, 2017(Rich et al, , 2018.…”

Section: The Relationship Between the "Bistable Transition" Mechanismmentioning

confidence: 99%

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Inhibitory Network Bistability Explains Increased Interneuronal Activity Prior to Seizure Onset

Rich

Chameh

Rafiee

et al. 2020

Front. Neural Circuits

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Recent experimental literature has revealed that GABAergic interneurons exhibit increased activity prior to seizure onset, alongside additional evidence that such activity is synchronous and may arise abruptly. These findings have led some to hypothesize that this interneuronal activity may serve a causal role in driving the sudden change in brain activity that heralds seizure onset. However, the mechanisms predisposing an inhibitory network toward increased activity, specifically prior to ictogenesis, without a permanent change to inputs to the system remain unknown. We address this question by comparing simulated inhibitory networks containing control interneurons and networks containing hyperexcitable interneurons modeled to mimic treatment with 4-Aminopyridine (4-AP), an agent commonly used to model seizures in vivo and in vitro. Our in silico study demonstrates that model inhibitory networks with 4-AP interneurons are more prone than their control counterparts to exist in a bistable state in which asynchronously firing networks can abruptly transition into synchrony driven by a brief perturbation. This transition into synchrony brings about a corresponding increase in overall firing rate. We further show that perturbations driving this transition could arise in vivo from background excitatory synaptic activity in the cortex. Thus, we propose that bistability explains the increase in interneuron activity observed experimentally prior to seizure via a transition from incoherent to coherent dynamics. Moreover, bistability explains why inhibitory networks containing hyperexcitable interneurons are more vulnerable to this change in dynamics, and how such networks can undergo a transition without a permanent change in the drive. We note that while our comparisons are between networks of control and ictogenic neurons, the conclusions drawn specifically relate to the unusual dynamics that arise prior to seizure, and not seizure onset itself. However, providing a mechanistic explanation for this phenomenon specifically in a pro-ictogenic setting generates experimentally testable hypotheses regarding the role of inhibitory neurons in pre-ictal neural dynamics, and motivates further computational research into mechanisms underlying a newly hypothesized multi-step pathway to seizure initiated by inhibition.

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Section: Methodsmentioning

confidence: 99%

Section: The Relationship Between the "Bistable Transition" Mechanismmentioning

confidence: 99%

Inhibitory Network Bistability Explains Increased Interneuronal Activity Prior to Seizure Onset

Rich

Chameh

Rafiee

et al. 2020

Front. Neural Circuits

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“…GABA are calculated by Equations (2)-(4). The newly added current I p M is described as follows (Rich et al, 2018)…”

Section: Populations Py and In In The Cortical Modulementioning

confidence: 99%

Effects of Cholinergic Neuromodulation on Thalamocortical Rhythms During NREM Sleep: A Model Study

Song

et al. 2020

Front. Comput. Neurosci.

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“…The measure used to quantify coherent activity in the simulated networks, here termed 216 a Synchrony Measure, is a slight adaptation of a commonly used measure created by 217 Golomb and Rinzel [40,41] that quantifies the degree of spiking coincidence in the 218 network. This particular implementation of this measure has been utilized in previous 219 studies [23,42,43] 220 Briefly, the measure involved convolving a Gaussian function with the time of each 221 action potential for every cell to generate functions V i (t). The population averaged 222 voltage V (t) was then defined as…”

mentioning

confidence: 99%

“…[74] imply that an 718 excitatory network made up of cells of the type studied here is highly unlikely to ever 719 synchronize. Similarly, while the Pyramidal Interneuron Network Gamma (PING) 720 mechanism is commonly cited as a mechanism causing synchronous oscillations in E-I 721 networks [16,72,75,76], recent work has revealed that the predictions of this mechanism 722 are altered by varying individual cellular properties and network connectivity [42,43]. consideration.…”

mentioning

confidence: 99%

Modeling implicates inhibitory network bistability as an underpinning of seizure initiation

Rich

Rafiee

et al. 2019

Preprint

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A plethora of recent experimental literature implicates the abrupt, synchronous activation of GABAergic interneurons in driving the sudden change in brain activity that heralds seizure initiation. However, the mechanisms predisposing an inhibitory network toward sudden coherence specifically during ictogenesis remain unknown. We address this question by comparing simulated inhibitory networks containing control interneurons and networks containing hyper-excitable interneurons modeled to mimic treatment with 4-Aminopyridine (4-AP), an agent commonly used to model seizures in vivo and in vitro. Our in silico study demonstrates that model inhibitory networks with 4-AP interneurons are more prone than their control counterparts to exist in a bistable state in which asynchronously firing networks can abruptly transition into synchrony due to a brief perturbation. We further show that perturbations driving this transition could reasonably arise in vivo based on models of background excitatory synaptic activity in the cortex. Thus, these results propose a mechanism by which an inhibitory network can transition from incoherent to coherent dynamics in a fashion that may precipitate seizure as a downstream effect. Moreover, this mechanism specifically April 11, 2019 1/36Recently, some studies of seizure initiation have shifted focus to over-activity of 25 inhibitory interneurons. This literature has yielded convincing evidence that 26 interneurons serve a causal role in seizure initiation [1,[8][9][10][11][12][13], laying the groundwork for 27 a novel hypothesis for seizure initiation (a "GABAergic initiation hypothesis") in which 28 synchronous activation of inhibitory interneurons precipitates the onset of a seizure, as 29 diagrammed in Fig 1 [12]. Given the contemporaneous nature of this hypothesis it is an 30ideal target for rigorous computational study; here, such research aims to unearth a 31 mechanism explaining the predisposition of inhibitory interneurons in a hyper-excitable 32April 11, 2019 2/36 environment to suddenly transition into synchrony, the necessary initial step in this 33 hypothesis. We thus focus on the earliest time in the transition to seizure and not 34 aspects of propagation and termination. 35The study of inhibitory network synchrony is decades old, dating back to the work of 36 Wang and Rinzel [14]. Various mechanisms have been proposed to explain the 37 generation of oscillations in purely inhibitory networks, the most prominent of which 38 may be the Interneuron Network Gamma (ING) mechanism [15-20]. Previous work has 39 shown that inhibitory networks built to examine population activity in an in vitro 40 hippocampal preparation manifest "sharp transitions" into coherent population activity 41 caused by a small, permanent increase to the external drive to the network [21]. 42 Additional studies have explored the effect of connection probabilities and cell 43 characteristics manifested by classifications of cell excitability on inhibitory network 44 synchrony [22, 23], and have noted that bist...

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Effects of Neuromodulation on Excitatory–Inhibitory Neural Network Dynamics Depend on Network Connectivity Structure

Cited by 16 publications

References 63 publications

Inhibitory Network Bistability Explains Increased Interneuronal Activity Prior to Seizure Onset

Inhibitory Network Bistability Explains Increased Interneuronal Activity Prior to Seizure Onset

Effects of Cholinergic Neuromodulation on Thalamocortical Rhythms During NREM Sleep: A Model Study

Modeling implicates inhibitory network bistability as an underpinning of seizure initiation

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