Roxana A. Stefanescu

Computational models of epilepsy

PURPOSE Approximately 30% of epilepsy patients suffer from medically refractory epilepsy, in which seizures can not controlled by the use of anti-epileptic drugs (AEDs). Understanding the mechanisms underlying these forms of drug-resistant epileptic seizures and the development of alternative effective treatment strategies are fundamental challenges for modern epilepsy research. In this context, computational modeling has gained prominence as an important tool for tackling the complexity of the epileptic phenomenon. In this review article, we present a survey of computational models of epilepsy from the point of view that epilepsy is a dynamical brain disease that is primarily characterized by unprovoked spontaneous epileptic seizures. METHOD We introduce key concepts from the mathematical theory of dynamical systems, such as multi-stability and bifurcations, and explain how these concepts aid in our understanding of the brain mechanisms involved in the emergence of epileptic seizures. RESULTS We present a literature survey of the different computational modeling approaches that are used in the study of epilepsy. Special emphasis is placed on highlighting the fine balance between the degree of model simplification and the extent of biological realism that modelers seek in order to address relevant questions. In this context, we discuss three specific examples from published literature, which exemplify different approaches used for developing computational models of epilepsy. We further explore the potential of recently developed optogenetics tools to provide novel avenue for seizure control. CONCLUSION We conclude with a discussion on the utility of computational models for the development of new epilepsy treatment protocols.

Tinnitus: Maladaptive auditory–somatosensory plasticity

Tinnitus, the phantom perception of sound, is physiologically characterized by an increase in spontaneous neural activity in the central auditory system. However, as tinnitus is often associated with hearing impairment, it is unclear how a decrease of afferent drive can result in central hyperactivity. In this review, we first assess methods for tinnitus induction and objective measures of the tinnitus percept in animal models. From animal studies, we discuss evidence that tinnitus originates in the cochlear nucleus (CN), and hypothesize mechanisms whereby hyperactivity may develop in the CN after peripheral auditory nerve damage. We elaborate how this process is likely mediated by plasticity of auditory-somatosensory integration in the CN: the circuitry in normal circumstances maintains a balance of auditory and somatosensory activities, and loss of auditory inputs alters the balance of auditory somatosensory integration in a stimulus timing dependent manner, which propels the circuit towards hyperactivity. Understanding the mechanisms underlying tinnitus generation is essential for its prevention and treatment. This article is part of a Special Issue entitled .

Listening to another sense: somatosensory integration in the auditory system

Conventionally, sensory systems are viewed as separate entities, each with its own physiological process serving a different purpose. However, many functions require integrative inputs from multiple sensory systems and sensory intersection and convergence occur throughout the central nervous system. The neural processes for hearing perception undergo significant modulation by the two other major sensory systems, vision and somatosensation. This synthesis occurs at every level of the ascending auditory pathway: the cochlear nucleus, inferior colliculus, medial geniculate body and the auditory cortex. In this review, we explore the process of multisensory integration from (1) anatomical (inputs and connections), (2) physiological (cellular responses), (3) functional and (4) pathological aspects. We focus on the convergence between auditory and somatosensory inputs in each ascending auditory station. This review highlights the intricacy of sensory processing and offers a multisensory perspective regarding the understanding of sensory disorders.

Stimulus-timing-dependent modifications of rate-level functions in animals with and without tinnitus.

Tinnitus has been associated with enhanced central gain manifested by increased spontaneous activity and sound-evoked firing rates of principal neurons at various stations of the auditory pathway. Yet, the mechanisms leading to these modifications are not well understood. In a recent in vivo study, we demonstrated that stimulus-timing-dependent bimodal plasticity mediates modifications of spontaneous and tone-evoked responses of fusiform cells in the dorsal cochlear nucleus (DCN) of the guinea pig. Fusiform cells from sham animals showed primarily Hebbian learning rules while noise-exposed animals showed primarily anti-Hebbian rules, with broadened profiles for the animals with behaviorally verified tinnitus (Koehler SD, Shore SE. J Neurosci 33: 19647-19656, 2013a). In the present study we show that well-timed bimodal stimulation induces alterations in the rate-level functions (RLFs) of fusiform cells. The RLF gains and maximum amplitudes show Hebbian modifications in sham and no-tinnitus animals but anti-Hebbian modifications in noise-exposed animals with evidence for tinnitus. These findings suggest that stimulus-timing bimodal plasticity produced by the DCN circuitry is a contributing mechanism to enhanced central gain associated with tinnitus.

NMDA receptors mediate stimulus-timing-dependent plasticity and neural synchrony in the dorsal cochlear nucleus

Auditory information relayed by auditory nerve fibers and somatosensory information relayed by granule cell parallel fibers converge on the fusiform cells (FCs) of the dorsal cochlear nucleus, the first brain station of the auditory pathway. In vitro, parallel fiber synapses on FCs exhibit spike-timing-dependent plasticity with Hebbian learning rules, partially mediated by the NMDA receptor (NMDAr). Well-timed bimodal auditory-somatosensory stimulation, in vivo equivalent of spike-timing-dependent plasticity, can induce stimulus-timing-dependent plasticity (StTDP) of the FCs spontaneous and tone-evoked firing rates. In healthy guinea pigs, the resulting distribution of StTDP learning rules across a FC neural population is dominated by a Hebbian profile while anti-Hebbian, suppressive and enhancing LRs are less frequent. In this study, we investigate in vivo, the NMDAr contribution to FC baseline activity and long term plasticity. We find that blocking the NMDAr decreases the synchronization of FC- spontaneous activity and mediates differential modulation of FC rate-level functions such that low, and high threshold units are more likely to increase, and decrease, respectively, their maximum amplitudes. Three significant alterations in mean learning-rule profiles were identified: transitions from an initial Hebbian profile towards (1) an anti-Hebbian; (2) a suppressive profile; and (3) transitions from an anti-Hebbian to a Hebbian profile. FC units preserving their learning rules showed instead, NMDAr-dependent plasticity to unimodal acoustic stimulation, with persistent depression of tone-evoked responses changing to persistent enhancement following the NMDAr antagonist. These results reveal a crucial role of the NMDAr in mediating FC baseline activity and long-term plasticity which have important implications for signal processing and auditory pathologies related to maladaptive plasticity of dorsal cochlear nucleus circuitry.

Muscarinic acetylcholine receptors control baseline activity and Hebbian stimulus-timing dependent plasticity in fusiform cells of the dorsal cochlear nucleus.

Cholinergic modulation contributes to adaptive sensory processing by controlling spontaneous and stimulus-evoked neural activity and long-term synaptic plasticity. In the dorsal cochlear nucleus (DCN), in vitro activation of muscarinic acetylcholine receptors (mAChRs) alters the spontaneous activity of DCN neurons and interacts with N-methyl-d-aspartate (NMDA) and endocannabinoid receptors to modulate the plasticity of parallel fiber synapses onto fusiform cells by converting Hebbian long-term potentiation to anti-Hebbian long-term depression. Because noise exposure and tinnitus are known to increase spontaneous activity in fusiform cells as well as alter stimulus timing-dependent plasticity (StTDP), it is important to understand the contribution of mAChRs to in vivo spontaneous activity and plasticity in fusiform cells. In the present study, we blocked mAChRs actions by infusing atropine, a mAChR antagonist, into the DCN fusiform cell layer in normal hearing guinea pigs. Atropine delivery leads to decreased spontaneous firing rates and increased synchronization of fusiform cell spiking activity. Consistent with StTDP alterations observed in tinnitus animals, atropine infusion induced a dominant pattern of inversion of StTDP mean population learning rule from a Hebbian to an anti-Hebbian profile. Units preserving their initial Hebbian learning rules shifted toward more excitatory changes in StTDP, whereas units with initial suppressive learning rules transitioned toward a Hebbian profile. Together, these results implicate muscarinic cholinergic modulation as a factor in controlling in vivo fusiform cell baseline activity and plasticity, suggesting a central role in the maladaptive plasticity associated with tinnitus pathology.NEW & NOTEWORTHY This study is the first to use a novel method of atropine infusion directly into the fusiform cell layer of the dorsal cochlear nucleus coupled with simultaneous recordings of neural activity to clarify the contribution of muscarinic acetylcholine receptors (mAChRs) to in vivo fusiform cell baseline activity and auditory-somatosensory plasticity. We have determined that blocking the mAChRs increases the synchronization of spiking activity across the fusiform cell population and induces a dominant pattern of inversion in their stimulus timing-dependent plasticity. These modifications are consistent with similar changes established in previous tinnitus studies, suggesting that mAChRs might have a critical contribution in mediating the maladaptive alterations associated with tinnitus pathology. Blocking mAChRs also resulted in decreased fusiform cell spontaneous firing rates, which is in contrast with their tinnitus hyperactivity, suggesting that changes in the interactions between the cholinergic and GABAergic systems might also be an underlying factor in tinnitus pathology.

Computational modeling of light activated ion channels

Channelrhodpsin-2 (ChR2) is a light sensitive ion channel protein currently investigated for millisecond time scale optogenetic control of neural activity [1]. Two competing mathematical models, a 3-state and a 4-state rate transition model are currently available to mimic the ChR2 photocurrent kinetics [2]. While both models are able to capture the key temporal features of ChR2 photocurrent in response to light stimulation pulses of different intensities and durations, little is known about their efficacy to model the neural response to light stimulation protocols of various frequencies and pulse width characteristics. Moreover, it is unclear to what degree the two models can capture the photocurrent kinetics of the recently engineered ChR2 mutants, designed to allow for more precise optical control of neural activity [3]. To address these issues, we investigate a 3-state and a 4-state transition rate model to mimic the photocurrent kinetic of wild type ChR2 (ChR2wt) and a newly validated ChR2 mutant with fast photocurrent kinetics (ChRETA) consistent with the experimental measurements in Gunaydin et al. [3]. We incorporate these models into a fast spiking hippocampal interneuron model [4] in order to examine to what degree the neural response to different experimental stimulation protocols can be successfully simulated. We find that the 3-state model can qualitatively reproduce the neural activity induced by periodic short time interval (2 ms) light pulse stimulation only for low frequencies (<20Hz). The model however fails to capture the experimentally observed features of neural response to higher frequencies (80 and 200 Hz) for both variants of ChR2 investigated. The 4-state model is able to reliably mimic the neural response to light pulse stimulation of all frequencies in both ChR2 variants. Furthermore, for ChR2wt, the 4-state model but not the 3-state model is able to reproduce both the burst-like neural firing activity induced by single, brief (2ms width) light pulses and the plateau potentials observed in neurons for high frequency (200 Hz) light stimulation. Both models were able to mimic the occurrence of missed spikes in ChR2wt when prolonged (60 light pulses) light stimulation is delivered, with better fidelity provided by the 4-state model. Finally, the 4-state model better captures the neural response to Poisson and Gaussian distributed light stimulation pulses. Motivated by the overall better performance of the 4-state model, we investigate the conditions under which a characteristic specific to the 3-state model, namely the mono-exponential decay of the ChR2 photocurrent kinetics (often reported in experimental literature) can occur in the 4-state model. Using analytical methods, we show that for each variant, the photocurrent component associated with the unreported decay constant is vanishingly small, which may explain the experimental difficulty in its empirical evaluation. In summary, we have systematically analyzed the 3-state and 4-state transition rate models for ChR2 photocurrent kinetics and demonstrated that independent of the variant, the 4-state model is able to better capture both qualitative and quantitative features of photocurrent kinetics and the neural response to several different light stimulation protocols. The results suggest that the 4-state transition rate model is a suitable candidate for a universal mathematical framework to model the photocurrent kinetic of ChR2 proteins.

Genesis of interictal spikes in the CA1: a computational investigation

1 J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA 2 Department of Otolaryngology, Kresge Hearing Research Institute, University of Michigan, Ann Arbor, MI, USA 3 Electrical and Computer Engineering, University of Florida, Gainesville, FL, USA 4 Department of Pediatrics, University of Florida, Gainesville, FL, USA 5 Qualcomm Corp R&D, San Diego, CA, USA