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Noebels JL, Avoli M, Rogawski MA, et al., editors. Jasper's Basic Mechanisms of the Epilepsies. 5th edition. New York: Oxford University Press; 2024. doi: 10.1093/med/9780197549469.003.0012
This chapter discusses the growing evidence that seizure generation and cognitive deficits have a similar pathological source characterized by, but not limited to, deficits in theta oscillations and their influence on interneurons that is part of a larger pathological brain network. The authors discuss new tools and techniques that are being used to identify this larger pathological network, how it overlaps with cognitive networks, and how therapies need to be developed that consider both the seizure network and the overlap with cognitive networks. A new framework is presented that describes oscillatory states in epilepsy as alternating between hyper- and hyposynchrony rather than solely the spontaneous transition to hyperexcitability characterized by the seizures. This framework suggests a pathological imbalance between excitation and inhibition in favor of synchronous inhibition during interictal theta oscillations that could account for both the seemingly spontaneous nature of seizures and comorbid cognitive deficits. The chapter concludes that there is a need to understand epilepsy as impacting extensive brain networks in order to optimize outcome for patients.
Epilepsy, characterized by an enduring predisposition to seizures, is one of the most common neurological diseases globally (Fiest et al., 2017; Beghi, 2020). Morbidity is compounded by neuropsychological symptoms, such as depression or memory loss, which, together with seizure frequency, impact quality of life (QOL). Epilepsy, including comorbid neuropsychological symptoms (Hermann et al., 2017), is a network phenomenon deserving network-focused treatment (Bettus et al., 2011; Coito et al., 2015; Kunieda et al., 2015; Kragel et al., 2017; Alarcón et al., 2018; Englot, 2020; Hallett et al., 2020). Often, seizures originate in a distinct part of the brain from other significant symptoms, such as depression or word-finding difficulties (Ung et al., 2017). Although seizures and neuropsychological symptoms may start in different places, there is evidence that they are both part of a pathologically hyperactive brain network (Kleen et al., 2010, 2013; Sreekumar et al., 2017; Ung et al., 2017; Kim et al., 2018; Colmers and Maguire, 2020). In this chapter, we explore how brain networks are affected in patients with epilepsy to generate seizures and comorbid neuropsychological symptoms in order to understand how to best optimize QOL.
Seizures are events that spread through the brain’s network of connections and create pathological activity (Lemieux et al., 2011). The emergence of tools to measure global and local brain connectivity as functions of dynamic integration/segregation, spatial importance, directional circuit flow patterns, and resilience to insult enable identification and assignment of weights to individual network elements. Network elements include nodes or hubs that are major transit points and are also likely to be seizure foci, and highways, or high-traffic paths, that maximally activate important network hubs (Rubinov and Sporns, 2010). Network architecture is revealed by constructing connectivity maps (Rubinov and Sporns, 2010; Zalesky et al., 2012; Hutchison et al., 2013; Sporns, 2013; Fornito et al., 2016) from criteria such as connectome-guided functional magnetic resonance imaging (fMRI) data (Calhoun et al., 2014), frequency band coherence (Burns et al., 2012, 2014; Jiang et al., 2019), frequency adaptive directed transfer function, graph metrics, multidimensional centrality measurements (Korzeniewska et al., 2008; Ewen et al., 2015; Skibski et al., 2019), clustering coefficients, efficiency of information flow between intra/extracranial electrodes across time (resting state to seizure stages), and cortico-cortical evoked potentials (CCEPs). CCEPs are of special interest as they can be recorded across intracranial electrodes to identify network hubs. These tools have enabled a more nuanced understanding of seizure generation and development.
Traditionally, epilepsy is defined by the seemingly spontaneous transition from normal interictal activity to a state of hyperexcitability defined by electrographic and motor seizures. However, recent investigations of temporal lobe epilepsy (TLE) have made it increasingly evident that seizure and non-seizure states are not as dichotomous as previously believed. In fact, epilepsy is associated with changes in brain networks that persist beyond seizure states. Interictal activity in animal models of epilepsy is different from brain activity of healthy animals. Furthermore, the transition to seizure is more fluid than originally described, such that the morphology of seizure-onset patterns can be identified seconds before ictal spiking (Grasse et al., 2013; Elahian et al., 2018; Misra et al., 2018). This transition can consist of different patterns of reorganization recruitment. For example, the activity of individual neurons during the transition to seizure is inhomogeneous in rats (Avoli et al., 2013; Grasse et al., 2013) and humans (Perucca et al., 2013). Specifically, multiple studies demonstrate that during the transition to seizures, some neurons increase their firing rate while others decrease it (Babb et al., 1987; Bower and Buckmaster, 2008; Truccolo et al., 2011; Bower et al., 2012; Grasse et al., 2013; Jiruska et al., 2013; Karunakaran et al., 2016), suggesting heterogeneous changes in firing rate rather than simple overall hyperexcitability. Studies from our lab and others (Arabadzisz et al., 2005; Avoli and de Curtis, 2011; Jefferys et al., 2012; Grasse et al., 2013; Perucca et al., 2013; Broggini et al., 2016; Behr et al., 2017) show that the critical factor in the transition to seizures is hypersynchrony, as measured by increases in synchrony within local field potentials (LFPs), between units and LFPs (i.e., spike-field coherence), and between units, especially in the theta band. Therefore, hypersynchrony, rather than simple hyperexcitability, is a better marker of the likelihood of a network transitioning to ictal activity (Wyler et al., 1982; Schwartzkroin and Haglund, 1986). Hypersynchrony is facilitated by clusters of neurons that are maximally connected to other sets of neurons which form hubs. Neurons that form hubs impact downstream neurons at many locations with high signal fidelity and relatively low signal threshold. In patients with epilepsy, the most influential hubs are their seizure foci, as shown by our group (Guo et al., 2020) and reported in literature (Ren et al., 2019). Knowledge of temporo-spatial seizure dynamics is important for optimizing timing/location(s) of neuromodulatory therapies, such as electrical brain stimulation (EBS), to mitigate seizure development.
While seizures may be the hallmark of TLE, the disease is also associated with several common comorbidities, including cognitive dysfunction and psychiatric disease (Chauvière et al., 2009; Giovagnoli et al., 2011, 2016; Avanzini et al., 2013; Parente et al., 2013; Swanson et al., 2014; Farina et al., 2015; Dinkelacker et al., 2016; Karunakaran et al., 2016; Hermann et al., 2017; Lee et al., 2017; Semple et al., 2018; Xu et al., 2018). Patient ratings of epilepsy-related morbidity are largely due to neurobiological, cognitive, and psychosocial symptoms experienced when the patient is not seizing (Wirrell et al., 1996, 1997; Devinsky and Najjar, 1999; Fisher et al., 2000; Yung et al., 2000; Battle, 2013), including fatigue, cognitive decline, depressed mood, or behavioral problems. Importantly, networks underlying the pathological brain states that cause neurologic and psychiatric health or sickness can be deciphered by the same methods for elucidating seizure networks (Bettus et al., 2008, 2011; Iwasaki et al., 2010; Keller et al., 2014; Kunieda et al., 2015; Usami et al., 2019; Colmers and Maguire, 2020) and, not surprisingly, these networks overlap. Therefore, activation of all or parts of the epileptic network below the seizure threshold can be experienced by patients as disturbance of mood (Fisher et al., 2000; Otero, 2009; Ramírez-Bermúdez et al., 2010; Ma et al., 2014), alertness/conscious awareness (Blumenfeld, 2012; Blumenfeld and Meador, 2014; Herman et al., 2017; Michel et al., 2019), or cognitive capacity (Kleen et al., 2010, 2013; Ung et al., 2017; Baud et al., 2018). A large body of exciting research is uncovering symptom-associated alterations in functional network signatures (Cole et al., 2014), including disrupted patterns of spatial concordance or functional connectivity (Madec et al., 2020) in patients with psychotic symptoms, redirected wave-like information flow in patients with decreased alertness (Blumenfeld, 2012; Blumenfeld and Meador, 2014; Herman et al., 2017; Michel et al., 2019), or decreased temporal lobe theta coherence in patients with cognitive sequelae.
Interestingly, cognitive disability may also be associated with pathological oscillations. Decreased burden of hypersynchronized high-frequency oscillations, which can be markers of ictogenic regions or regions involved in seizure spread, is correlated with improved cognitive function (Liu and Parvizi, 2019). In contrast, cognitive disability is also correlated with hyposynchrony in the theta band during interictal periods. This is important because theta oscillations play a key role in synaptic plasticity and cognition (Wallenstein and Hasselmo, 1997; Buzsáki, 2002). In fact, direct lesions of the medial septal nucleus (MSN) or the dorsal fornix reduce hippocampal theta oscillations and impair spatial memory performance (Winson, 1978; Chrobak et al., 1989; Givens and Olton, 1990) in rodents while electrical stimulation of forniceal fibers enhances memory (Koubeissi et al., 2013) by enhancing long-lasting hyperpolarization mechanisms that underlie theta oscillation production (Smerieri et al., 2010; Toprani and Durand, 2013; Neske, 2015; Malezieux et al., 2020). Moreover, a concomitant decrease in theta oscillations and impaired spatial learning can be observed in models of traumatic brain injury, including injury resulting in epilepsy (Chauviere et al., 2009; Kitchigina et al., 2013; Lee et al., 2017). Similar to findings in rats, theta oscillations have been observed in humans across a variety of cognitive tasks, including recognition (Raghavachari et al., 2001; Hsieh et al., 2011), recall (Sederberg et al., 2003), and virtual spatial navigation tasks (Kahana et al., 1999; de Araujo et al., 2002; Caplan et al., 2003; Watrous et al., 2011; Watrous et al., 2013). Moreover, while there are clear epilepsy-related changes in synchrony that impair learning and memory, the effects of therapeutic interventions on cognition are often overlooked. Current antiepileptic drugs (AEDs) reduce excitability by acting on specific cellular mechanisms, such as enhancing GABA-mediated chloride currents or reducing glutamate-mediated currents, sodium currents, or voltage-gated calcium currents (primarily T-type) (Macdonald et al., 1995; Bromfield, 2006). Similarly, the three currently FDA-approved therapies involving electrical brain stimulation (EBS)—vagal nerve stimulation, deep-brain stimulation, and responsive neurostimulation—are also designed to lower excitability (Salanova et al., 2015; Geller et al., 2017). Depending on the location and stimulation paradigm, lowering excitability can exacerbate cognitive impairments (Trimble, 1987), resulting in noncompliance due to unwanted side effects (Buck et al., 1997; Hovinga et al., 2008). Therefore, in this chapter, we suggest that, while a tonic reduction in excitability does reduce hypersynchrony and, therefore, prevent or reduce seizures, it may also favor a hyposynchronous state, which may explain patient reports of increased cognitive disability as well as diminished QOL.
To understand the cellular and network mechanisms that can, on the one hand, lead to hypersynchrony and seizures while, on the other, hyposynchrony and cognitive deficits, requires the development of a new framework that can account for both phenomena rather than hyperexcitability alone. This new framework would recognize the overlap and would promote the development of therapies, whether future drug development or neuromodulation paradigms, that ameliorate both seizure frequency and cognitive deficits. There are certainly oscillations across multiple frequency bands, and potential oscillatory interactions that may contribute to icto-genesis, and certainly to arousal and cognitive function. However, theta frequency oscillations, and synchrony with these oscillations, play a key and specific role in modulating seizures as well as learning and plasticity. Therefore, in this chapter, we examine the evidence that epilepsy is part of a larger pathological brain network that includes pathological theta synchrony with interneurons, transitioning from relatively slow dynamics to faster dynamics that can explain both spontaneous seizures and cognitive deficits. Specifically, short and defined epochs of hypersynchrony result in the generation and spread of seizures while extended periods of hyposynchrony result in the reduced potential for plasticity and therefore cognitive disorders. Understanding these mechanisms may lead to therapies that can reduce the hypersynchrony while maintaining physiological levels of synchrony that do not interfere with cognitive processing.
Here, we posit that epilepsy therapies of the future, such as neuromodulation with EBS, can aim for neuropsychological rehabilitation in addition to seizure control. Considering treatment of neuropsychological symptoms when choosing therapy for patients can dramatically improves QOL relative to only considering seizure symptoms. Moreover, restoring physiological function to networks outside seizure foci also improves the degree of seizure freedom achieved. Brain remodeling after epilepsy surgery shows increased restoration of physiological functioning of neuropsychological networks. In fact, the degree of network normalization measured after epilepsy surgery is predictive of seizure freedom after surgery (Ung et al., 2017; Englot et al., 2018; Boerwinkle et al., 2019; Englot, 2020; Gotman, 2020). Recent studies have shown significant effects of EBS for cognitive rehabilitation, including memory enhancement (Suthana and Fried, 2014), mood modulation (Rose et al., 2008), and restoration of consciousness (Michel et al., 2019). Functional brain networks often have intrinsic resonant frequencies, or the frequency of input that is most likely to influence that network’s behavior (Hutcheon and Yarom, 2000; Entz et al., 2014; Kragel et al., 2017; Megevand et al., 2017), such as theta frequencies that are relevant for many cognitive functions (e.g., memory; Hutcheon and Yarom, 2000). However, whether EBS enhances or disrupts cognitive function depends on fine-tuning of stimulation parameters, including the location, laterality, frequency, duration, timing, or task dependence, and work to achieve optimal stimulation is ongoing (Halgren et al., 1985; Coleshill et al., 2004; Toprani and Durand, 2013; Koubeissi et al., 2013; Suthana and Fried, 2014; Jacobs et al., 2016, no date; Inman et al., 2017; Corey et al., 2018; Ezzyat et al., 2018; Kim et al., 2018). With informed tuning, long-term EBS for seizure treatment, applied at high and low frequencies, has been shown to improve cognition as well as patient QOL ratings (Koubeissi et al., 2013; Loring et al., 2015; Meador et al., 2015). Yet little work has been done to specifically identify therapeutic electrical stimulation that may be used both for seizure treatment and neuropsychological rehabilitation in epilepsy patients. However, we expect that designing EBS seizure-treatment paradigms based on an epilepsy patient’s unique hyperactive network components, including the hubs that broadcast information from a specific location to other regions in the network along highways that modulate the activation of relevant, downstream network hubs, will optimize outcome. This is plausible because a wide range of EBS frequencies, amplitudes, and patterns effectively reduce seizures (Granata et al., 2009; Salanova, 2018) and are candidates to also improve neuropsychological symptoms. Furthermore, EBS protocols that have been shown to significantly decrease epileptic activity mirror electrical stimulation protocols that have been shown to enhance memory or other neuropsychological symptoms (Coito et al., 2015; Sreekumar et al., 2017). By taking account of patients’ chief comorbid epilepsy symptoms in addition to seizure burden, and guided by the new knowledge highlighted in this chapter, it is expected that dual-purpose network-based minimally invasive electrotherapy targeting highly influential parts of seizure networks will improve patients’ QOL beyond seizure outcomes.
There is abundant evidence that high power theta oscillations are dominant during the transition to seizures (Fig. 12–1; Turski et al., 1983; Butuzova and Kitchigina, 2008; Grasse et al., 2014; Broggini et al., 2016). Moreover, these theta oscillations that precede seizures are more rhythmic, having a narrower theta frequency band, compared to interictal theta oscillations (Testani et al., 2016). Since single neuron firing patterns can be coherent with ongoing theta oscillation and either increase (theta-on pyramidal cells or interneurons; Colom and Bland, 1987; Smythe et al., 1991; Bland et al., 1999) or decrease (theta-off cells; Buzsáki, 2002) their firing rate while roughly one-third of CA1 interneurons are independent of ongoing theta activity (Czurko et al., 2011), how these specific neuronal subtypes fire in relation to theta rhythms (i.e., varying levels of synchrony) has been shown to be important for understanding the difference between physiological and pathological oscillations. In fact, multiple studies show that during the transition to seizures, whether neurons increase or decrease their firing rate is related to that cell’s theta-related neuron subtype (Lévesque et al., 2011, 2012; Toyoda et al., 2015; Samiee et al., 2018). Moreover, the firing rate of pyramidal cells is typically slower prior to seizure onset than during interictal periods, regardless of theta cell type. In fact, pyramidal cells in the CA3 increase their firing rates after the onset of rhythmic LFP spiking (Grasse et al, 2013; Toyoda et al., 2015).
Theta oscillations precede majority of seizures. Left, gray bars indicate total number of seizures followed by each behavior. Color bars indicate the number of seizures with at least one non-theta to theta transition in the 2 minutes preceding rhythmic (more...)
Conversely, the relationship between interneuron firing patterns and seizures is more complex. In vitro studies identified that activation of hippocampal (Velazquez and Carlen, 1999; Ziburkus et al., 2006; and Fujiwara-Tsukamoto et al, 2010) and entorihinal (de Guzman et al., 2008; Gnatkovsky et al., 2008; Uva, Avoli and de Curtis, 2009; Avoli and de Curtis, 2011; Jefferys et al., 2012; Panuccio et al., 2012; Uva et al., 2015) interneuron networks are potentially responsible for initiation of rhythmic ictal spiking leading up to seizure activity. For example, interneuron activity is maximal just before the onset of rhythmic ictal spikes in the local field of hippocampal slices. In addition, cortical pyramidal cells are recruited into the epileptiform event only after the failure of existing inhibitory restraint mechanisms (Trevelyan et al., 2007; Levesque et al., 2016; Aracri et al., 2018). However, it should be noted that this may be the case for low-voltage, fast-onset events only, while hypersynchronous-onset discharges rely on the activation of pyramidal cells (Shiri et al., 2015). Induced seizures have also been studied in the intact brain preparation, where interneuron activity was also shown to be related to the generation of seizure-like-events (Bragin et al., 1997; Timofeev et al., 2002; Gnatkovsky et al., 2008). These results suggest a complex role for interneurons in the generation of seizures that was subsequently studied in vivo prior to spontaneous seizure in both animals and humans.
In animal models of spontaneous seizures, approximately 40% of CA3 interneurons, predominately theta-on interneurons, increase their firing rate at seizure onset (Grasse et al., 2013; Toyoda et al., 2015; Karunakaran et al., 2016) (Fig. 12–2). In the entorhinal cortex in both rats and humans, only interneurons showed phase-locked relationship with ongoing oscillatory activity in the theta range during the tonic phase (Levesque et al., 2016). Moreover, similar patterns of activity were found in the dentate gyrus, CA1, and subiculum, with interneurons showing an increase in firing rate in the seconds preceding an ictal event and the patterns of activity were highly consistent from event to event (Toyoda et al., 2015). Here, too, there was evidence of cell-type specificity (Toyoda et al., 2015). Still, nearly a quarter of CA1 interneurons became inactive in the same period. These combined results suggest that identifying the roles of each neuronal subtype, as well the relationship between their firing pattern changes and ongoing theta oscillations, is critical to understanding the cellular mechanisms underlying the transition to seizures and for developing therapeutic interventions.
A. LFP trace leading to an example seizure and raster plots of a pyramidal cell (blue) and interneuron (red) firing. Time 0 refers to the onset of rhythmic ictal spiking. Insets show waveforms of an action potential in four wires of the tetrode (more...)
In addition to changes in individual firing rates of neuronal types during ictogenesis, there are more complex changes as the network transitions from interictal to ictal spiking, including changes in coherence (Fig. 12–3). For example, during the narrowing of the theta frequency band prior to ictal spiking onset, there is a reliable and concomitant increase in synchrony between interneurons and the ongoing theta (Grasse et al., 2013) followed by an increase in gamma power. As a consequence, interneuron spiking switches its entrainment with the ongoing theta to entrainment with this gamma power increase (Grasse et al., 2013; Toyoda et al., 2015; Lopez-Pigozzi et al., 2016). Over the subsequent 10 seconds, interneurons make a final transition in their firing pattern coherence from the gamma oscillations to the emergent ictal spikes, with their firing rate dropping below baseline levels. This transition is unlikely to be due to the slowing of the gamma frequency that occurs as the level of excitation to interneurons decreases (Traub et al., 1996), since the firing rate of the interneurons remains high during this period. Moreover, the transition to a lower frequency is not a continual shift, but rather reflects the emergence of a separate oscillatory mode since gamma oscillations and ictal spiking coexist (Kopell et al., 2000). This transition could be due to a gradual alteration of a network parameter such as the accumulation of extracellular potassium (Shin et al., 2010), deficits in somatic or dendritic inhibitory efficacy (Cossart et al., 2001; Wendling et al., 2002), or changes in slow potassium.
Spike field coherence (A, B) and LFP power (C, D) of neurons detected during firing rate increases occurring in baseline windows (bold lines) and in the seizure-onset window (light lines). Error bars are the standard error over all neurons of a cell (more...)
Detailed inspection of the enhanced coherence between interneurons and ongoing oscillations reveals that these average increases in coherence are not the result of sustained increases, but rather originate from short bursts of coherence for each neuron (Grasse et al., 2013). Typically, the higher the frequency, from theta to gamma, the shorter the interval. Moreover, the fraction of interneurons that show an increase in coherence in each of these oscillation windows is greater than during interictal periods. In summary, during the transition to seizures, not only are there changes in firing rates, but more interneurons show a higher level of phase-locking to the ongoing dominant local field oscillations as compared to interictal periods.
As ictal oscillations emerge, they entrain both pyramidal cells and interneurons into a hypersynchronous state as demonstrated in CA3 (Grasse et al., 2013; Toyoda et al., 2015), CA1 (Toyoda et al., 2015), and entorhinal cortex (Levesque et al., 2016). Early in this phase, pyramidal cell firing rates increase as interneuron firing rates drop, suggesting they are synchronous with different phases of the ictal spiking (Grasse et al., 2013; Toyoda et al., 2015). Together, these findings suggest a series of state transitions dominated by changes in entrainment of interneurons with the ongoing LFP, starting with theta, followed by a peak in gamma power and finally ictal spiking oscillations. Therefore, a combination of changes in interneuronal activity (both increases and decreases) and spike-field synchrony plays an important role in recruiting a network into ictal spiking.
The causal mechanisms underlying these changes in CA3 could be partly due to a dysfunction of normal entorhinal cortex operations (Basso et al., 1995; Bartolomei et al., 2005; Kumar and Buckmaster, 2006; Kispersky et al., 2010; Herrington et al., 2015) as evidenced from entorhinal cortex lesion studies (Cappaert et al., 2009). Either alternatively to, or in conjunction with, dysfunction of entorhinal driven theta, the medial septum is also likely to play a part in the theta synchrony we observe. Highly rhythmic theta oscillations concurrent with rhythmic unit activity have been observed in the hippocampus and/or medial septum (Butuzova and Kitchigina, 2008; Popova et al., 2008; Kitchigina et al., 2013) prior to seizures induced in the septum. This highly rhythmic theta activity was considered to be mechanistically different from native theta oscillations, which suppress interictal spikes (Colom, 2006) and could also be responsible for at least some of the cognitive deficits identified. Regardless of an entorhinal or septal origin of the coherent activity, the result is likely to be increased synaptic plasticity, a process highly favored by theta rhythmicity (Larson et al., 1986; Diamond et al., 1988; Huerta and Lisman, 1993; Natsume and Kometani, 1997). The resulting potentiation of synapses between small networks of cells in the hippocampus may create a pathologically interconnected network (Bragin et al., 2005; Karunakaran et al., 2016) that would impact both seizure generation and cognitive deficits.
While hypersynchrony is the hallmark of epilepsy and transition to seizure, it is critical to consider which changes in interictal neural activity may be connected to neuropsychological comorbidities or even disease progression. For example, when comparing recordings from the CA3 hippocampus between sham and epileptic rats, a reduction in theta power and a general slowing of theta rhythms, as well as the overall firing rate of cells recorded is observed (Karunakaran et al., 2016). For both kainic acid (Riban et al., 2002; Arabadzisz et al., 2005; Dugladze et al., 2007) and pilocarpine (Colom et al., 2006; Chauviere et al., 2009; Marcelin et al., 2009; Karunakaran et al., 2016; Lee et al., 2017) models of TLE in rodents, a significant reduction of theta power follows both acutely induced status epilepticus as well as chronic spontaneous seizures. Changes in oscillatory power occur bilaterally, in the dorsal (Arabadzisz et al., 2005; Colom, 2006) and ventral hippocampus (Arabadzisz et al., 2005; Dugladze et al., 2007) as well as the medial septum (Arabadzisz et al., 2005; Colom et al., 2006). Theta oscillations during interictal periods within hippocampal CA3 are also slower in epileptic animals compared to controls, consistent with observations in CA1 hippocampus of kainate-treated (Inostroza et al., 2013) or pilocarpine-treated (Marcelin et al., 2009) animals. The reasons for this decreased theta frequency could be a reduction in theta resonance (Marcelin et al., 2009). Alternately, significant neuronal loss in either the medial septum or the hippocampus, and in particular GABAergic cells (Kitchigina et al., 2013), can lead to a diminished or altered theta directly or indirectly through reorganization of the surviving cells in these networks.
Along with changes in oscillations, the activity of both pyramidal cells and interneurons is reduced in the CA3 of epileptic animals compared to controls during the interictal period (Karunakaran et al., 2016). Lateral septal neurons, a target of hippocampal glutamatergic neurons that play a key role in theta frequency modulation (Alonso and Kohler, 1982; Alonso and Frotscher, 1989; Jinno and Kosaka, 2002), also have lower firing rates in epileptic animals (García-Hernández et al., 2010), presumably due to reduced hippocampal feedback. This general decrease in activity that is consistent throughout preictal periods during both theta and non-theta epochs suggests that it may be mediated by anatomical or physiological alterations or long-term functional and synaptic changes (Cavalheiro, 1996; Curia et al., 2008).
There are two intriguing exceptions to the general reduction in activity. The first is that the firing rate of theta-off pyramidal cells is state dependent—it is pathologically low during theta epochs (Karunakaran et al., 2016) but not during non-theta periods. The impact of this is unclear, in part because the role of these cells is not well understood. However, since pyramidal cells are more inhibited during theta than in control animals, theta-off pyramidal cells in the epileptic CA3 are excessively inhibited during theta epochs, contributing to the ineffective transmission of information to downstream neurons.
The second is that the firing patterns (firing rate and entrainment) of theta-on interneurons are unchanged regardless of theta state (Karunakaran et al., 2016). It is possible that this cell type is functionally preserved in epilepsy or that there is minimal loss of these neurons. It has been reported that, in rat models of epilepsy, there is a selective preservation of hippocampal (Cossart et al., 2001; Ratte et al., 2006) and medial septum interneurons (Cossart et al., 2005; Majczynski Henryk et al., 2005; Garrido Sanabria et al., 2006). Regardless, the critical observation is a relatively high firing rate of theta-on interneurons in the epileptic CA3 network compared to other cell types. Since CA3 interneurons are almost certainly inhibitory interictally, this exclusive maintenance of theta-on interneuron firing rate demonstrates higher levels of inhibition during theta compared to healthy controls.
As described above, firing rates of most neurons, except theta-on interneurons, are decreased in epileptic animals compared to healthy controls. Moreover, theta-off pyramidal cells decrease their firing rate compared to healthy controls during interictal theta epochs but not during non-theta epochs. However, the effectiveness of synaptic barrages depends not only on the overall number of postsynaptic potentials but also on their temporal pattern. To assess the impact of this reduction in firing rate during theta, the phase locking of neuronal activity during oscillations can be estimated by the coherence between the oscillation (field) and the single-neuron spike times (spike-field coherence). We investigated the relationship between those interneurons that modulate their firing rate with theta (theta-on and theta-off) as well as those that did not (theta-unrelated) and found that both theta-off and theta-unrelated interneuron subtypes, but not pyramidal cells, have increased theta band spike-field coherence interictally in CA3 of epileptic rats compared to controls (Karunakaran et al., 2016). Therefore, there are subtype-specific differences in both interictal firing rate and spike-field coherence of interneurons but not pyramidal cells compared to control animals.
As hippocampal interneurons are the exclusive targets of medial septal GABAergic projections (Freund and Antal, 1988; Tóth et al., 1997), the increased coherence could be due to enhanced theta coherence between medial septum and hippocampus (Towle et al., 1998; Holtkamp et al., 2005; Avoli and de Curtis, 2011) or hypersynchrony in superficial layers of upstream entorhinal cortex (Kobayashi et al., 2003; Kumar and Buckmaster, 2006; Kumar et al., 2007). Understanding the origins of the altered coherence, or potential targets for mediating coherence, is critical for both understanding mechanisms related to ictogenesis as well as potential therapeutic targets. For example, during interictal periods, this increased synchrony during theta could help to compensate for lower overall firing rates of interneurons and help to explain both the seemingly spontaneous occurrence of seizures and comorbid cognitive deficits. First, the coherent interneuron action potentials could be more effective due to temporal coincidence of their inhibitory postsynaptic potentials in downstream neurons compared to a similar number of noncoherent potentials. Second, for pyramidal cells embedded in a pathologically connected network, there is no such compensation and no opportunity for coherent excitation. Therefore, during interictal periods, the increased interneuron synchrony would be sufficient to keep pyramidal cell firing in-check during theta so that networks prone to ictogenesis do not continuously transition to seizure. Moreover, this suppression of pyramidal activity could, in some animals, be overpowering and simultaneously induce cognitive deficits (see next section). In support of our proposed framework, these findings demonstrate a pathological imbalance between excitation and inhibition in favor of synchronous inhibition during interictal theta oscillations that could account for both the seemingly spontaneous nature of seizures and comorbid cognitive deficits.
There is considerable evidence that lesions to the hippocampus, and even the septohippocampal circuit, can lead to cognitive dysfunction (Buzsaki, 2005). Some of these changes in behavior may be directly related to the inability to generate a memory (i.e., the loss of significant place cells). However, one other potential consequence of neuronal loss is that the injury will result in altered oscillations, preventing the remaining intact circuit from functioning optimally. At the level of individual synapses, for example, there is evidence that timing high-frequency bursts to the phase of theta results in the greatest amount of potentiation (Larson et al., 1986; Gerstein and Kirkland, 2001; Orr et al., 2001). Extending this idea into our proposed framework, the ability to form and recall memories requires the integration of activity and plasticity across multiple brain regions. The role of theta oscillations in facilitating plasticity and learning have been well described in rodent models (Buzsaki, 2005). For example, theta oscillations facilitate the timing of neuronal activity across distal regions of the brain, thereby promoting learning and memory (Vertes and Kocsis, 1997; Buzsaki, 2005; Hasselmo, 2005; Siapas et al., 2005; Harris and Gordon, 2015). More specifically, there is evidence that oscillations play a role in coordinating activity between the hippocampus and prefrontal cortex (PFC), as evidenced by enhanced theta coherence during spatial working memory and decision-making tasks in the rat (Jones and Wilson, 2005; Benchenane et al., 2010). Importantly, pharmacological inactivation of the MSN using tetracaine results in diminished hippocampal theta and is correlated with deficits in tasks such as the Morris water maze (McNaughton et al., 2006). Similarly, injection of either muscimol or scopolamine into the MSN results in attenuated theta and impaired cognitive performance (Givens and Olton, 1990, 1994). Akin to pharmacological manipulations, large lesions of the MSN result in reduced hippocampal theta oscillations and alter spatial learning. Similar lesions of the septum that do not result in altered theta oscillations do not affect spatial learning (Winson, 1978). Critically, models of neurological disease also can result in attenuated oscillations and cognitive dysfunction. For example, we, as well as others, have reported that both rats with traumatic brain injury (Lee and Heckman, 2013) and rats that have experienced status epilepticus (Lee et al., 2017) or have chronic epilepsy (Chauviere et al., 2009; Kitchigina et al., 2013) exhibit reduced hippocampal theta oscillations and impaired spatial learning (Fig. 12–4).Taken together, these pharmacological, lesion, and disease-related data demonstrate the functional link between theta oscillations and cognitive function.
Example traces from hippocampal depth electrodes in patients (A) performing a virtual reality spatial learning task and rats (B) performing the Barnes maze spatial learning task. A comparison of normalized log power (C) demonstrates that while theta (more...)
There is now mounting evidence from electrocorticography (ECoG) recordings in epilepsy patients that there is a similar relationship of theta oscillations with episodic memory and spatial navigation as has been observed in rodent models (Burke et al., 2014; Comper et al., 2017; Rzezak et al., 2017; Tramoni-Negre et al., 2017; Vaz et al., 2017; Viskontas et al., 2016; Watrous et al., 2013b; Young et al., 2018) (Fig. 12–4). Also consistent with rodent data, individual human hippocampal neurons phase-lock to theta oscillations (Jacobs et al., 2007), with optimal spatial performance during periods of high (as compared to low) theta power (Merkow et al., 2014; Bohbot et al., 2017). Finally, there is clinical evidence that individuals with diminished theta oscillations do not perform as well on spatial tasks [162]. For example, studies of healthy and depressed patients (Cornwell et al., 2008; Kumar et al., 2009) demonstrate a clear correlation between diminished theta oscillations and poor spatial learning in a virtual water maze paradigm (Cornwell et al., 2008). In studies of aging, there was also a significant relationship between theta power and spectral coherence across age, with older subjects having both less theta and a decline in cognitive performance (Dias et al., 2015). At present, the role of theta oscillations in learning and the relationship of attenuated oscillations to cognitive dysfunction are well-accepted. However, there remain many questions related to the role of theta to cognitive processes, including the significance of specific oscillatory frequencies, coherence, spike timing, and cross-frequency coupling.
Earlier in this chapter we detailed how high-power theta oscillations precede ictal events and evidence that stimulating at theta frequencies can attenuate evoked seizures. For example, activating the cholinergic circuit either with microinjections of carbachol or electrical stimulation of the MSN in the range of 4–8 Hz evoke hippocampal theta oscillations and inhibit pentylenetetrazol-induced seizures (Miller et al., 1994). Similar microinjections of carbachol also induce theta oscillations and inhibit behavioral and electrographic seizures in acutely exposed pilocarpine rats (Colom, 2006). In addition, both spontaneous occurrences of theta and induced theta via tail pinch reduce markers of epileptiform activity (Colom, 2006).
These data suggest that pathological theta could be the cause of both seizure generation and cognitive deficits and, therefore, restoring appropriate rhythmic theta can prevent seizures and improve cognitive outcome in animals with epilepsy. For example, 7.7 Hz theta stimulation of the MSN generated the highest power hippocampal theta oscillations for the least amount of input current (Gray and Ball, 1970; Ball and Gray, 1971) and was the best treatment for restoring physiological theta after inactivation of the MSN. Furthermore, fixed 7.7 Hz stimulation drove hippocampal oscillations and improved spatial learning performance. However, irregular theta stimulation that resulted in an average frequency of 7.7 Hz was less effective, resulting in minimal rhythmicity and no behavioral improvement, and 100 Hz stimulation was ineffective (Lee et al., 2015). Following pilocarpine-induced status epilepticus resulting in a significant acute reduction in theta power, animals demonstrated a significantly worse search strategies in a Barnes maze (Lee et al., 2017; Izadi et al., 2019). Stimulation of the MSN at 7.7 Hz, however, led to a significant improvement in search strategy. Interestingly, stimulation of sham rats with otherwise normal theta oscillations led to a significant decrease in object exploration and a trend toward worse performance on the Barnes maze as compared to nonstimulated shams (Lee et al., 2017). Along with pharmacology, electrical neuromodulation shows promise to drive theta oscillations and test the framework that hyposynchrony is related to depressed cognitive function in rodents and even, in some cases, seizures.
Over 3.4 million people are currently diagnosed with epilepsy in the United States (Zach and Kobau, 2017), resulting in an estimated economic impact of over $9.5 billion annually (Yoon et al., 2009). Partial-onset epilepsies represent more than two-thirds of all cases, and TLE is the most prevalent subtype (Semah et al, 1998). Approximately 30%–40% of patients with TLE are refractory to anticonvulsant medications, representing 80% of the total economic burden (Begley, 2000; Laxer, 2014). Most patients with intractable TLE experience persistent altered cognitive function due to recurrent seizures as well as drug-related side effects (Trimble, 1987). Animal studies, outlined above, suggest that eliminating hyperexcitability may prevent hypersynchronous states that transition to seizures; this approach may also induce a general state of hyposynchrony that could exacerbate cognitive dysfunction. Moreover, there are no clinical interventions that employ specific anatomical targets and stimulation parameters that alleviate both seizures and cognitive impairments associated with TLE. Throughout this chapter we have demonstrated that periods of hypersynchrony, including high-power theta oscillations, increased theta coherence, and spike-frequency coherence in interneurons are associated with ictogenesis. We have also cited an extensive literature that suggests that hyposynchrony, and specifically hyposynchrony related to theta oscillations, is associated with cognitive dysfunction. Finally, we point out that there is overlap in the networks associated with a patient’s seizure and networks underlying cognitive function. Therefore, there is a need to understand the effect of epilepsy on broader neuronal networks to identify therapies that attenuate, or hopefully eliminate, seizure frequency while also ameliorating cognitive deficits. We propose that this framework could help develop novel therapies, whether new antiepileptic drugs or deep brain stimulation paradigms, to modulate theta synchrony, both within oscillations across the brain and between ongoing oscillation and single neuron activity. This approach would allow for reduction of both seizures and epilepsy-related comorbidities, resulting in an overall improvement in behavioral and cognitive function.
This is an open access publication, available online and distributed under the terms of a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International licence (CC BY-NC-ND 4.0), a copy of which is available at https://creativecommons.org/licenses/by-nc-nd/4.0/. Subject to this license, all rights are reserved.
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