Hippocampal Oscillations, Mechanisms (PING, ING, Sparse)

Wal, Marije ter; Tiesinga, Paul

doi:10.1007/978-1-4614-6675-8_475

Cited by 5 publications

(10 citation statements)

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“…Of particular interest in the computational study of purely inhibitory networks is their tendency to synchronize, which dates back to the work of Wang and Rinzel (1992). Various mechanisms have been proposed to explain the generation of oscillations in purely inhibitory networks, the most prominent of which may be the Interneuron Network Gamma (ING) mechanism (Traub et al, 1998;Whittington et al, 2000;Bartos et al, 2007;Tiesinga and Sejnowski, 2009;Wang, 2010;ter Wal and Tiesinga, 2015). Previous work has shown that inhibitory networks built to examine population activity in an in vitro hippocampal preparation manifest "sharp transitions" into coherent population activity caused by a small, permanent increase to the external drive to the network .…”

Section: Introductionmentioning

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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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: Introductionmentioning

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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“…Up to the aforementioned frequency of ~22 Hz in period 2, both the frequency and spectral power of the rhythmic network activity increased with increasing light intensities ( n = 8 from 6 animals, Figure 2F ). Thus, the frequency increased with increasing spectral power, representing a relationship that is typical for P-I oscillations (ter Wal and Sejnowski, 2014 ). Such a relationship was likewise observed for the oscillatory activity in period 1 (data not shown).…”

Section: Resultsmentioning

confidence: 80%

“…As shown in Figure 2B (arrow heads), the optogenetically triggered oscillations mostly comprised clearly visible population spikes, suggesting an involvement of rhythmic synchronous firing of pyramidal neurons. Such ensemble activity is characteristic for P-I oscillations (ter Wal and Sejnowski, 2014 ). Due to their higher stability and spectral power in period 2 (Figure 2C ), all following analyses of the oscillations were done for this time frame.…”

Section: Resultsmentioning

confidence: 99%

“…Two experimentally induced types of this self-produced rhythmicity (and most likely also natural CA1 gamma oscillations) involve feedback inhibition of pyramidal neurons (Whittington et al, 1997 ; Buzsáki and Wang, 2012 ; Pietersen et al, 2014 ), but it remains unclear whether area CA1 harbors the circuitry for a generation of prototypic pyramidal-interneuron network (P-I) gamma oscillations. Such oscillations must exclusively arise from sustained suprathreshold depolarization and feedback inhibition of pyramidal cells (Bartos et al, 2007 ; Tiesinga and Sejnowski, 2009 ; ter Wal and Sejnowski, 2014 ), without direct excitatory effects of the induction agents/techniques on the mediating GABAergic interneurons (cf., Whittington et al, 1997 ; Pietersen et al, 2014 ; Yi et al, 2014 ), and could impact network oscillations in the PrC (Bilkey and Heinemann, 1999 ; Fell et al, 2001 ). Rationale for this assumption is given by the facts that area CA1 and the directly interconnected subiculum send excitatory projections to the PrC (van Groen and Wyss, 1990 ) and that pyramidal cells persistently fire in a synchronized rhythmic manner during P-I oscillations (Tiesinga and Sejnowski, 2009 ; ter Wal and Sejnowski, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

“…Such oscillations must exclusively arise from sustained suprathreshold depolarization and feedback inhibition of pyramidal cells (Bartos et al, 2007 ; Tiesinga and Sejnowski, 2009 ; ter Wal and Sejnowski, 2014 ), without direct excitatory effects of the induction agents/techniques on the mediating GABAergic interneurons (cf., Whittington et al, 1997 ; Pietersen et al, 2014 ; Yi et al, 2014 ), and could impact network oscillations in the PrC (Bilkey and Heinemann, 1999 ; Fell et al, 2001 ). Rationale for this assumption is given by the facts that area CA1 and the directly interconnected subiculum send excitatory projections to the PrC (van Groen and Wyss, 1990 ) and that pyramidal cells persistently fire in a synchronized rhythmic manner during P-I oscillations (Tiesinga and Sejnowski, 2009 ; ter Wal and Sejnowski, 2014 ). In the present study, we tested these scenarios in NEX-Cre-Channelrhodopsin-2 (ChR2) mice, which selectively express the excitatory opsin ChR2 in forebrain glutamatergic cells (and thus in CA1 pyramidal neurons), but not in inhibitory interneurons (Goebbels et al, 2006 ; Section “Results”).…”

Section: Introductionmentioning

confidence: 99%

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Local Optogenetic Induction of Fast (20–40 Hz) Pyramidal-Interneuron Network Oscillations in the In Vitro and In Vivo CA1 Hippocampus: Modulation by CRF and Enforcement of Perirhinal Theta Activity

Dine

Genewsky

Hladky

et al. 2016

Front. Cell. Neurosci.

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The neurophysiological processes that can cause theta-to-gamma frequency range (4–80 Hz) network oscillations in the rhinal cortical-hippocampal system and the potential connectivity-based interactions of such forebrain rhythms are a topic of intensive investigation. Here, using selective Channelrhodopsin-2 (ChR2) expression in mouse forebrain glutamatergic cells, we were able to locally, temporally precisely, and reliably induce fast (20–40 Hz) field potential oscillations in hippocampal area CA1 in vitro (at 25°C) and in vivo (i.e., slightly anesthetized NEX-Cre-ChR2 mice). As revealed by pharmacological analyses and patch-clamp recordings from pyramidal cells and GABAergic interneurons in vitro, these light-triggered oscillations can exclusively arise from sustained suprathreshold depolarization (~200 ms or longer) and feedback inhibition of CA1 pyramidal neurons, as being mandatory for prototypic pyramidal-interneuron network (P-I) oscillations. Consistently, the oscillations comprised rhythmically occurring population spikes (generated by pyramidal cells) and their frequency increased with increasing spectral power. We further demonstrate that the optogenetically driven CA1 oscillations, which remain stable over repeated evocations, are impaired by the stress hormone corticotropin-releasing factor (CRF, 125 nM) in vitro and, even more remarkably, found that they are accompanied by concurrent states of enforced theta activity in the memory-associated perirhinal cortex (PrC) in vivo. The latter phenomenon most likely derives from neurotransmission via a known, but poorly studied excitatory CA1→PrC pathway. Collectively, our data provide evidence for the existence of a prototypic (CRF-sensitive) P-I gamma rhythm generator in area CA1 and suggest that CA1 P-I oscillations can rapidly up-regulate theta activity strength in hippocampus-innervated rhinal networks, at least in the PrC.

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A hypothesis for theta rhythm frequency control in CA1 microcircuits

Skinner

Rich

Lunyov

et al. 2020

Preprint

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Computational models of neural circuits with varying levels of biophysical detail have been generated in pursuit of an underlying mechanism explaining the ubiquitous hippocampal theta rhythm. However, within the theta rhythm are at least two types with distinct frequencies associated with different behavioural states, an aspect that must be considered in pursuit of these mechanistic explanations. Here, using our previously developed excitatory-inhibitory network models that generate theta rhythms, we investigate the robustness of theta generation to intrinsic neuronal variability by building a database of heterogeneous excitatory cells and implementing them in our microcircuit model. We specifically investigate the impact of three key ‘building block’ features of the excitatory cell model that underlie our model design: these cells’ rheobase, their capacity for post-inhibitory rebound, and their spike-frequency adaptation. We show that theta rhythms at various frequencies can arise dependent upon the combination of these building block features, and we find that the speed of these oscillations are dependent upon the excitatory cells’ response to inhibitory drive, as encapsulated by their phase response curves. Taken together, these findings support a hypothesis for theta frequency control that includes two aspects: (i) an internal mechanism that stems from the building block features of excitatory cell dynamics; (ii) an external mechanism that we describe as ‘inhibition-based tuning’ of excitatory cell firing. We propose that these mechanisms control theta rhythm frequencies and underlie their robustness.

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Hippocampal Oscillations, Mechanisms (PING, ING, Sparse)

Cited by 5 publications

References 0 publications

Inhibitory Network Bistability Explains Increased Interneuronal Activity Prior to Seizure Onset

Inhibitory Network Bistability Explains Increased Interneuronal Activity Prior to Seizure Onset

Local Optogenetic Induction of Fast (20–40 Hz) Pyramidal-Interneuron Network Oscillations in the In Vitro and In Vivo CA1 Hippocampus: Modulation by CRF and Enforcement of Perirhinal Theta Activity

A hypothesis for theta rhythm frequency control in CA1 microcircuits

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