Seizure activity is commonly considered to arise from an imbalance of excitation and inhibition in vulnerable neural circuits, leading to unconstrained activity that self-organizes into patterns of hypersynchrony. One mechanism of such an imbalance may be a transient loss of GABAergic inhibition (Ziburkus et al., 2006). Acute blockade of GABA receptors rapidly initiates seizure activity (Rose and Blakemore, 1974; Treiman, 2001), suggesting the necessity of synaptic inhibition to maintain healthy activity patterns. Previous work has also highlighted the potential preictal contribution of excitatory GABAergic effects due to Cl- accumulation (Cossart et al., 2005; Palma et al., 2006; Miles et al., 2012) or loss of inhibition due to depletion of GABAergic release (Zhang et al., 2012). Interneuron firing may also transiently cease during ictal events as a result of depolarization block (Ziburkus et al., 2006; Cammarota et al., 2013; Kim and Nykamp, 2017). Developmental dysregulation of inhibitory interneurons causes chronic epileptic disorders (Lau et al., 2000; Cobos et al., 2005; Rossignol et al., 2013; Tai et al., 2014), and interneurons also appear to be particularly sensitive to seizure-related damage (Sloviter, 1987; de Lanerolle et al., 1989; Robbins et al., 1991; Rice et al., 1996; Gibbs et al., 1997; Cossart et al., 2001). However, the circuit mechanisms underlying seizure initiation in vivo and the specific role of GABAergic interneurons remain largely unknown.

Work from in vitro and in vivo animal models has suggested that different neural populations may have distinct and complex patterns of preictal activity during seizure initiation. Putative interneurons in multiple hippocampal regions are reported to exhibit increases and/or decreases in firing rates prior to seizure initiation (Grasse et al., 2013; Toyoda et al., 2015). In vitro recordings during seizure-like events further suggest interleaved bursts of firing by interneurons and excitatory neurons (Ziburkus et al., 2006). In the cortex, fast-spiking, putative inhibitory interneurons may exhibit enhanced preictal firing (Timofeev et al., 2002; Gnatkovsky et al., 2008), but recent work using population imaging largely observed increased activity following seizure onset (Khoshkhoo et al., 2017). Putative fast-spiking interneurons in human cortex may also exhibit increased preictal firing rates (Truccolo et al., 2011). In comparison, previous work has largely found increased preictal firing of putative excitatory hippocampal neurons (Cymerblit-Sabba and Schiller, 2010; Jiruska et al., 2010; Fujita et al., 2014), but several reports have highlighted mixed populations, with some neurons increasing and some decreasing firing prior to seizure (Bower and Buckmaster, 2008; Toyoda et al., 2015). The trajectory of interneuron activity and the relationship between excitatory and inhibitory neurons during seizure initiation thus remain unclear.

One key challenge in examining the respective roles of excitatory and inhibitory cells in seizure initiation is the diversity of inhibitory interneurons. Neocortical GABAergic interneurons exhibit a wide variety of morphologies, molecular markers, and activity patterns, and make synapses on different subcellular domains of target pyramidal cells (Rudy et al., 2011). In the hippocampus, these include the soma-targeting, axo-axonic and basket cells that co-express the calcium binding protein parvalbumin (PV) and the dendrite-targeting O-LM and bistratified interneurons that co-express the peptide somatostatin (SST) (Buhl et al., 1994; Sik et al., 1995; Klausberger et al., 2003; Petilla Interneuron Nomenclature Group et al., 2008; Lapray et al., 2012). Despite their divergent cellular properties, these cell classes are difficult to identify in vivo using traditional recording methods. Conflicting previous reports of the preictal activity of putative interneurons may thus be due in part to recordings of mixed neural populations.

Here, we used optogenetic tools to identify, track, and probe two distinct populations of hippocampal interneurons, the PV- and SST-expressing cells, in two models of acute chemoconvulsive seizure initiation in vivo. Chemoconvulsant models are reliable and consistent across animals and provide a window into the transition from healthy to pathological neural activity, separating interneuron activity and inhibitory influence in the initial transition to ictal activity from alterations in interneuron activity that are known to occur as a result of seizure-induced cell death or sprouting. The inhibitory influence of PV and SST interneuron firing on nearby neurons remains largely intact throughout the preictal and early ictal periods, suggesting that seizure activity does not arise from a failure of GABAergic inhibition from these cells. Instead, PV and SST cells exhibit cell-type-specific differences in their preictal activity and in the evolution of their sensitivity to input. Our findings suggest that the onset of ictal activity is associated with dysregulation of the distinct roles these interneuron populations play in the local hippocampal circuit.

To examine the preictal activity of identified hippocampal interneurons, we performed tetrode recordings of isolated single units and local field potentials (LFPs) from hippocampal CA1 in lightly anesthetized mice expressing Channelrhodopsin-2 (ChR2) in target cells. Seizure activity was induced with systemic administration of the chemoconvulsant Pentylenetetrazol (PTZ) (Figure 1A). During the baseline period, we identified PV- (n = 56 cells in 45 mice) and SST- (n = 42 cells in 34 mice) expressing interneurons in PV-Cre/ChR2 or SST-Cre/ChR2 mice, respectively, by their short-latency, low-jitter responses to blue light (Figure 1B; see Materials and methods) (Cardin et al., 2009; Lima et al., 2009). On average, PV cells displayed narrow spike waveforms, whereas SST cells exhibited broader waveforms (Figure 1C and Figure 1—figure supplement 1A-B). However, there was extensive overlap of waveform characteristics among the populations (Figure 1—figure supplement 1A-B), indicating that spike waveform alone is not sufficient to distinguish cell types under these conditions. Histological analysis confirmed that the two identified interneuron populations were largely non-overlapping within CA1 (Figure 1—figure supplement 1C-K). In some experiments, unidentified cells (n = 49 cells in 26 mice) were simultaneously recorded along with ChR2-tagged units in PV-Cre and SST-Cre mice or in the pyramidal cell layer of wild-type mice (Figure 1—figure supplement 1A-B). A subset of these unidentified cells (n = 26 cells in 16 mice) were regular spiking (RS), putative excitatory cells with characteristic broad spike waveforms and relatively low baseline firing rates (Figure 1C and Figure 1—figure supplement 1).

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In an initial series of experiments, we assessed the spontaneous activity of these three cell classes during a baseline period and four preictal periods leading into PTZ-induced seizure under light anesthesia (Figure 1D). For each animal, the preseizure period was divided into four equally spaced quartiles based on the latency from chemoconvulsant administration to ictal onset. PV, SST and RS cells exhibited increased firing rates following PTZ administration, but showed markedly different firing rate trajectories (Figure 1E). Strikingly, we found that most PV cells strongly increased their firing rate in the last preictal period as compared to the first (94.4%, p<0.001, Binomial test) or third (83.3%, p<0.001). In contrast, this sharp, late increase in firing rate was not observed in SST or RS cells (Figure 1E). Increased firing of PV, SST, and RS cells was independent of the latency to ictal onset (Figure 1—figure supplement 2A-E) and was observed in the absence of significant changes in spike waveform amplitude over time (Figure 1—figure supplement 2F). There was no difference in the preictal trajectory of FS and non-FS PV interneurons (Figure 1—figure supplement 2C).

To identify common elements across different models of seizure initiation, we compared our PTZ data with recordings from identified interneurons during acute Pilocarpine-induced seizures. We observed a similar increase in PV cell firing rates during the late preictal period preceding Pilocarpine-induced seizures (Figure 1—figure supplement 2G-J), suggesting that this is not a unique feature of PTZ-induced seizures. As in the PTZ model, there was no difference in the preictal trajectory of FS and non-FS PV interneurons (Figure 1—figure supplement 2K).

In a separate series of experiments, we recorded from identified PV (n = 12 cells in eight mice), SST (n = 10 cells in nine mice), and RS (n = 28 cells in 14 mice) cells in awake head-fixed mice during PTZ seizure initiation (Figure 1F, Figure 1—figure supplement 3). We found firing rate trajectories similar to those observed in the anesthetized paradigm for all cell classes. Both PV and SST interneuron firing increased during the preictal period, as did RS cell firing. However, only PV interneurons showed a sharp increase in firing rate immediately prior to seizure onset (Figure 1F).

We next examined whether interneuron firing remained elevated during the ictal period. Rigorous spike waveform identification after ictal onset is highly challenging. However, we were able to track a subset of recorded neurons through an initial 60 s ictal period (Figure 2A). We found that after ictal onset, PV and SST firing decreased from the preictal peak back to baseline levels (Figure 2B–C). In contrast, RS cells continued to fire at elevated rates (Figure 2D), suggesting a sustained early ictal increase in the activity of excitatory, but not inhibitory, neurons.

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To assay whether the observed changes in the activity of interneurons were associated with altered inhibition of their targets, we measured the impact of ChR2-evoked interneuron spiking on the firing rate of nearby RS cells. During baseline activity, we found that the firing rate of RS cells decreased following ChR2-evoked PV and SST cell spiking (Figure 3A–B). We compared the impact of ChR2-evoked inhibition during the four preictal periods and an additional period immediately following ictal onset. RS firing suppression was not significantly changed across the preictal and early ictal periods as compared to baseline when the PV cells were driven by optogenetic stimulation (see Materials and methods; Figure 3C–D, Figure 3—figure supplement 1). RS suppression by SST cell spiking was likewise maintained throughout preictal and early ictal periods. We further measured RS suppression in awake animals during seizure initiation. We were not able to maintain high-quality recordings after ictal onset in awake animals. However, RS suppression in response to PV and SST spiking was consistently observed during the preictal period of awake seizure initiation (Figure 3D).

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We next explored whether preictal changes in interneuron activity levels were accompanied by changes in the temporal spike pattern. Immediately preceding ictal onset in both anesthetized and awake animals, PV, but not SST or RS, cell firing became significantly more regular (i.e., less bursty) (Figure 4A–B, Figure 4—figure supplement 1E). In addition, PV cells showed an increased tendency to fire spikes separated by short (<10 ms) inter-spike-intervals (ISI; Figure 4—figure supplement 1). Unidentified cells with narrow spikes did not exhibit changes in firing rate, firing regularity, or ISI statistics (Figure 4—figure supplement 1B-D).

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PV and SST interneurons normally exhibit temporally patterned activity and highly precise entrainment to hippocampal gamma and theta rhythms (Klausberger et al., 2003; Klausberger et al., 2005; Tukker et al., 2007; Diba et al., 2014). We therefore computed the mean spike field coherence (SFC) for PV, SST and RS cells during baseline activity and across the four preictal periods (Figure 4C, Figure 4—figure supplement 1). We observed a prominent peak in the 20 – 28 Hz band of the LFP (Chen et al., 2011; Cabral et al., 2014; Sauer et al., 2015) under baseline and preictal conditions (Figure 1A). PV cells showed a peak in SFC in the 20 – 28 Hz frequency band that decreased significantly during the preictal period (Figure 4C–D) in the absence of any loss in LFP power or changes in SFC in the theta or high gamma bands, other prominent hippocampal rhythms associated with interneuron activity (Figure 4—figure supplement 1F-H). In contrast, neither SST nor RS cells showed a change in SFC across the preictal periods, suggesting a specific decoupling of PV cells from their normal temporal relationship with the local hippocampal network during the onset of ictal activity (Figure 4—figure supplement 1F-H).

To examine whether preictal changes in interneuron output were accompanied by changes in sensitivity to input, we tested the responses of PV and SST cells to optogenetic stimulation during each preictal period. We measured the probability of interneuron spiking in response to light pulses of varying intensity (Figure 5A). PV cells showed no progressive change in spike probability over the preictal period (Figure 5B–C). In contrast, SST cells showed an increase in the slope of their response curve and a decrease in their maximal response probability (Rmax) across the preictal periods. Changes in interneuron sensitivity to input were not affected by seizure latency (Figure 5—figure supplement 1). Together, these data suggest a progressive preictal attenuation of the response of SST cells to input, potentially limiting their recruitment by network inputs.

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During spontaneous and evoked neural activity, excitation and inhibition are tightly coupled in amplitude (Shu et al., 2003; Haider et al., 2006; Xue et al., 2014) and temporal pattern (Pouille and Scanziani, 2001; Wehr and Zador, 2003; Higley and Contreras, 2006; Cardin et al., 2010). Disruption of the excitatory-inhibitory balance profoundly alters circuit function (Fritschy, 2008; Žiburkus et al., 2013) and is hypothesized to play a significant role in the pathophysiological patterns of brain activity leading to the onset of seizure. The transition to ictal activity has been characterized in a variety of ways in rodents, including by manual validation (Henderson et al., 2014), threshold detection of increased EEG power (Khoshkhoo et al., 2017), and combined measurement of EEG power trajectory and spectral features (Krook-Magnuson et al., 2014). However, the patterns of activity underlying these transitions from stable to epileptiform activity are not well understood.

In the current study, where we utilized an acute chemoconvulsant seizure induction, the onset of the ictal period was defined quantitatively by increased LFP amplitude, which largely corresponded to the first ictal spike. These early events occurred in advance of full ictal recruitment. We found that PV- and SST-expressing interneurons and RS, putative excitatory cells exhibited different preictal firing rate trajectories. SST and RS cells showed an early, modest increase in firing, whereas >90% of PV cells exhibited a late increase in firing immediately before ictal onset. During the early ictal period, PV and SST cell firing rates returned to baseline levels, whereas RS cell firing remained elevated. These changes in PV and SST cell firing rates occurred in the absence of changes in the impact of ChR2-evoked inhibition on local RS cells. Overall, these results suggest that the initial changes in network activity leading to early stages of seizure initiation may not be associated either with an overall failure of GABAergic inhibition from PV or SST cells or with unconstrained excitation. However, we note that our findings do not preclude additional impairments in inhibitory function at the time of ictal recruitment or later in the ictal period.

Fast-spiking, PV-expressing interneurons are coupled to both high-frequency and theta rhythms in the hippocampus, and are thought to contribute to maintaining the fine temporal organization of excitatory-inhibitory interactions (Buzsáki et al., 2003; Csicsvari et al., 2003; Klausberger et al., 2003; Diba et al., 2014; Amilhon et al., 2015; Forro et al., 2015; Huh et al., 2016). The earliest preictal change we observed was a loss of the strong spike-field coherence of PV cell spiking to a prominent low-gamma band previously observed in mouse hippocampus (Chen et al., 2011; Cabral et al., 2014; Sauer et al., 2015). Previous work has suggested that increased inhibitory synaptic activity or the onset of depolarization block in fast-spiking interneurons could precipitate seizure onset (Velazquez and Carlen, 1999; Timofeev et al., 2002; Ziburkus et al., 2006; Fujiwara-Tsukamoto et al., 2007; Gnatkovsky et al., 2008; Cammarota et al., 2013; Kim and Nykamp, 2017), and we found that the onset of ictal spikes occurred immediately after a sharp increase in PV interneuron spiking in both anesthetized and awake animals. However, we found no evidence for decreased interneuron spike amplitude prior to ictal onset, suggesting that these interneurons did not enter depolarization block prior to ictal onset. Late preictal increases in PV interneuron firing could lead to irregular firing patterns or bursts in excitatory neurons, potentially resulting in hyper-synchronized, pathological entrainment of excitatory activity (Shiri et al., 2015; Yekhlef et al., 2015; Avoli et al., 2016).

In contrast to the PV interneurons, SST interneurons showed a sustained elevation of preictal firing without a late increase in firing rate preceding the transition to ictal activity. SST interneurons did not show a change in the overall temporal pattern of their spiking or entrainment to specific hippocampal rhythms. However, optogenetic stimulation revealed that SST, but not PV, cells exhibited altered sensitivity to input and a decreased maximum response to inputs during the late preictal period. OLM cells, the primary group of SST neurons targeted in our experiments, receive input from CA1, but not CA3 or the entorhinal cortex (Blasco-Ibáñez and Freund, 1995). They innervate the distal tuft dendrites of local excitatory pyramidal neurons, providing potent recurrent feedback within the local circuit (Bloss et al., 2016). SST inhibition restrains the occurrence of hippocampal pyramidal neuron bursts, which promote highly effective transmission to downstream targets (Lisman, 1997; Royer et al., 2012), and may regulate plateau potentials and plasticity in pyramidal cell dendrites (Takahashi and Magee, 2009; Lovett-Barron et al., 2012). SST cells show a preictal decrease in dynamic range and loss of ability to respond to depolarizing inputs, potentially leading to nonlinear amplification of excitatory activity in the local hippocampal circuit.

Previous work has found extensive heterogeneity in preictal firing rate trajectories of extracellularly recorded putative excitatory and inhibitory neurons. Intracellular and extracellular recordings of fast-spiking, putative PV interneurons have found increased preictal firing rates in cortical networks (Timofeev et al., 2002; Gnatkovsky et al., 2008) or a transient increase in firing immediately preceding ictal onset for some hippocampal cells (Grasse et al., 2013; Toyoda et al., 2015). To our knowledge, there are no previous data on the preictal firing rate trajectories of SST interneurons, although recent work in motor cortex found general population recruitment of both PV and SST interneurons following contralateral seizure onset (Khoshkhoo et al., 2017). In turn, some reports suggest increased preictal firing of regular spiking putative excitatory neurons in hippocampus (Cymerblit-Sabba and Schiller, 2010; Jiruska et al., 2010; Fujita et al., 2014), but others find a mix of increases and decreases within multiple hippocampal areas (Bower and Buckmaster, 2008; Toyoda et al., 2015). Although the findings of a number of studies in both neocortex and hippocampus are thus consistent with inhibitory disruption, it also remains possible that the mechanisms underlying seizures in these areas are different.

We found that identification by action potential waveform or baseline firing rate was not a reliable indicator of cell identity for hippocampal PV interneurons. In addition, in agreement with previous work (Klausberger et al., 2003; Halabisky et al., 2006; Katona et al., 2014), we found that SST interneurons exhibited varied action potential durations and could not be distinguished from regular spiking excitatory neurons by waveform. Optical tagging with Cre-dependent ChR2 allowed identification of each population despite overlapping action potential characteristics, and we found that the three cell classes we examined demonstrated distinct trajectories. Indeed, >90% of PV interneurons exhibited a characteristic increase in firing immediately prior to the first ictal spike, suggesting that some of the heterogeneity observed in previous studies may arise from a mixed population of unidentified cells.

We examined interneuron activity in two chemoconvulsant models of acute induction of status epilepticus. These models provide insight into the mechanisms by which normal, healthy neural circuits transition to pathological patterns of activation, although the precise commonality of circuit-level mechanisms underlying induced and spontaneous seizures has not been fully explored. We used both PTZ, thought to be a competitive antagonist of the GABA_A receptor (Huang et al., 2001), and Pilocarpine, a nonselective muscarinic acetylcholine receptor agonist (Turski et al., 1989). Despite distinct pharmacological mechanisms, we found similar trajectories for PV interneuron activity in both models, as well as in awake animals, suggesting that preictal increases in PV activity may be a common element of acute seizure initiation. However, the exact timing of interneuron activity varied slightly across models. Because these drugs arrive rapidly in the brain at effective concentrations following systemic administration (Yonekawa et al., 1980; Ramzan and Levy, 1985), it is unlikely that the progression of interneuron firing changes resulted from gradual accumulation of chemoconvulsants in neural tissue. Our experiments were largely conducted under anesthesia, which could potentially prolong the preictal period and reduce seizure activity (Murao et al., 2002; Fang and Wang, 2015; Grover et al., 2016). However, the light anesthesia we used allowed normal spontaneous hippocampal firing patterns to be maintained and promoted short ictal onset delays similar to those in awake animals. Furthermore, we observed similar PV and SST trajectories in awake and anesthetized animals.

One potential function of inhibition during seizure is the restraint of ictal activity. The spreading ictal wavefront generates feedforward excitation, which recruits powerful feedforward inhibition that may restrict the postsynaptic recruitment of spiking activity. Synaptic inhibition restrains the spread of ictal activity in the cortex (Trevelyan et al., 2006; Trevelyan et al., 2007; Schevon et al., 2012; Sessolo et al., 2015), and surround inhibition around epileptic foci has been observed in animal and human seizures (Prince and Wilder, 1967; Schwartz and Bonhoeffer, 2001; Timofeev et al., 2004; Trevelyan et al., 2006; Trevelyan et al., 2007). We observed preictal increases in both PV and SST firing rates, raising the possibility that compensatory increases in inhibition transiently restrain oncoming ictal events. However, the increasing loss of normal temporal structure and input sensitivity by the PV and SST interneuron populations, respectively, may contribute to the transition to a pathological state.

Overall, our data suggest that cell-type-specific disruption of finely tuned interneuron relationships with the local hippocampal circuit may contribute to reorganization of inhibitory activity prior to seizure initiation. These findings highlight the complex involvement of distinct GABAergic interneuron populations in early stages of pathological activity in the hippocampal circuit. Indeed, although the PV and SST populations encompass a large proportion of hippocampal interneurons, other inhibitory cell types may be differentially engaged by seizure initiation and remain to be investigated.

Source data files are included for each figure and supplemental figure. Raw data are too large (750Gb) to include within the manuscript but are available on request as compiled sets of raw data and intermediate analysis files.

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Author details

1. Mitra L Miri

   Department of Neuroscience, Yale University School of Medicine, New Haven, United States

   Contribution

   Formal analysis, Methodology, Writing—original draft, Writing—review and editing

   Contributed equally with

   Martin Vinck

   Competing interests

   No competing interests declared

2. Martin Vinck

   Department of Neuroscience, Yale University School of Medicine, New Haven, United States

   Contribution

   Formal analysis, Writing—original draft, Writing—review and editing

   Contributed equally with

   Mitra L Miri

   Competing interests

   No competing interests declared

3. Rima Pant

   Department of Neuroscience, Yale University School of Medicine, New Haven, United States

   Contribution

   Data curation, Formal analysis

   Competing interests

   No competing interests declared

4. Jessica A Cardin

   1. Department of Neuroscience, Yale University School of Medicine, New Haven, United States
   2. Kavli Institute for Neuroscience, Yale University, New Haven, United States

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Methodology, Writing—original draft, Project administration, Writing—review and editing

   For correspondence

   jess.cardin@yale.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-8209-5466

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