Ivan Soltesz - US grants

DESCRIPTION (provided by applicant): Febrile (fever-induced) seizures are the most common forms of childhood seizures, affecting three percent to five percent of infants and young children in the United States and worldwide. In spite of the extremely high incidence of fever-induced seizures, whether and how febrile seizures in the developing brain alter neuronal circuits is not well understood. Indeed, one of the most controversial issues in epilepsy is the relationship of convulsions in infancy to the subsequent development of temporal lobe epilepsy. Retrospective clinical studies indicated that a large fraction of patients with intractable temporal lobe epilepsy have a history of febrile seizures as infants. However, prospective studies have failed to find this association. Recently, an appropriate-aged rodent model of hyperthermia-induced seizures has been introduced, suitable for studying the mechanisms and sequelae of febrile seizures. Under the previous award, we used this model of experimental febrile seizures to determine that experimental febrile seizures in infant rats resulted in a persistent, presynaptic increase in inhibition, but concurrent changes in specific postsynaptic ion channels (h-channels) paradoxically converted the potentiated inhibition to hyperexcitability. Here we propose to test the hypothesis that hyperthermia-induced seizures result in persistent, hyper-synchronous inhibitory synaptic inputs to principal cells in the hippocampus. The specific aims will be tested using patch clamp electrophysiological, immunocytochemical and computational modeling techniques. Two types of controls will be employed: 1) age-matched, normothermic sham controls, and 2) age-matched, hyperthermic controls, in which the seizures were blocked using pharmacological agents. Preliminary data indicate that a specific type of interneuron is involved in the generation of hyper-synchronous inhibitory inputs to postsynaptic cells after experimental febrile seizures. Additional preliminary results suggest that activation of cannabinoid-1 receptors can potently modulate the hyper-synchronous inhibitory inputs to principal cells after the seizures, in agreement with recent reports showing the expression of cannabinoid-l receptors on specific interneuronal axon terminals. The data obtained from the proposed experiments will determine how long-term alterations in the interactions of interneurons and principal cells can be regulated, and will help to identify novel mechanisms that could be targeted for anti-epileptic drug therapies in children.

DESCRIPTION (provided by applicant): Temporal lobe epilepsy is the most common form of epilepsy in adults. Currently available anti-epileptic drugs often have significant and debilitating side-effects, and temporal lobe epilepsy frequently becomes resistant to drug therapy, presenting an enormous social and medical problem. The central idea behind the proposed research is that it may be possible to achieve seizure control by transiently inhibiting, only at critical moments, the activity of a low number of unique neurons that may be primarily responsible to triggering seizures in the limbic system. Our recent large-scale computational modeling studies have shown that rare, abnormal, super- connected, hub-like neurons may play a key role in seizure initiation. Subsequently, such hub cells have been demonstrated in the healthy developing hippocampus, and it has been shown that modulation of single hub cells in slices can block the spontaneous bursting activity of the entire network. Here we propose to use novel optogenetic approaches to selectively inhibit abnormal hub-like cells in the dentate gyrus and entorhinal cortex of epileptic adult mice in vivo in order to prevent the hyper-activation of the commissural-associational and temporo-ammonic pathways within the entorhino-hippocampal network specifically at the onset of spontaneous recurrent seizures. Because the manipulation will affect only a few cells in the entire limbic system in a temporally selective manner, effective seizure control may be achieved with minimal effects on the normal information processing of the circuit. If successful, the proposed research will demonstrate a fundamentally novel approach to achieving the goal of no seizures, no side-effects for the treatment of epilepsy.

The hippocampus in mammals is a brain area important for learning and memory that is also implicated in several major neurological and psychiatric disorders including epilepsy, autism, schizophrenia and Alzheimer's disease. Prior research revealed that learning and memory-related information processing in the hippocampus critically depends on clock-like, rhythmic electrical signals elicited by an adjacent brain structure called the septum. However, how the oscillatory neuronal activity emerges from the closely interconnected neuronal networks of the septum and the hippocampus is not understood. The current project will employ novel, uniquely high-throughput experimental approaches in mice integrated with innovative, biologically realistic, large-scale supercomputer-based theoretical modeling techniques to identify key mechanisms underlying rhythmic electrical signal generation in septo-hippocampal circuits. The project represents a potentially major milestone in the development of biologically based realistic computer models of the brain, as it would allow the generation and testing of hypotheses concerning network mechanisms of behaviorally relevant oscillatory neuronal activity with unparalleled biological realism, precision and speed. In addition, the experimental knowledge base and the large-scale computational brain models will be placed in open-source databases (including ModelDB for network models at http://senselab.med.yale.edu/modeldb/, and Neuromorpho for biological structural data at http://neuromorpho.org/) that are freely accessible for the unrestricted use by the scientific community. This project involves extensive postdoctoral training in neuroinformatics.

This award is co-funded by NSF's Office of the Director, International Science and Engineering, and a companion project is being funded by the French National Research Agency (ANR).

? DESCRIPTION (provided by applicant): The function of a brain region is an emergent property of many cell types. The criteria needed to understand a network have been established in studies of invertebrate simple networks, but there has not yet been an attempt to provide such a full, mechanistic understanding of any network in the vertebrate brain. We believe that the time is now ripe for such an effort. Specifically, we propose to understand how the CA3 network in the hippocampus generates sharp-wave-ripples (SWR). These events are of great interest because of their cognitive function: they represent replay of episodic memory sequences and are required for subsequent memory recall, as demonstrated at the behavioral level. Our efforts to understand the SWR will build on previous work establishing the cell types of the hippocampus. However, to meet the criteria for understanding, a great deal of additional information about connectivity and intrinsic properties of cells must be obtained. We will use recently developed large-scale electrical and optical recording methods and ontogenetic to obtain this information. In addition, several new methods/tools will be developed. Notably, we propose to optimize a novel synapse localization optical method to obtain high-throughput cell type-specific information about the connective of the CA3 network. We will also construct the first full-scale computational model of the CA3 region of the hippocampus, in which every cell and synaptic connection is explicitly represented. This strictly data-driven, full-scale model will provide a widely applicable tool for synthesizing experimental results and testing our ability to understand the principles that underlie SWR generation.

? DESCRIPTION (provided by applicant): Temporal lobe epilepsy (TLE) is the most common epilepsy in adults. TLE is often refractory to current anti- epileptic drugs, and systemic treatments are frequently accompanied by significant negative side effects. However, the cellular and circuit mechanisms underlying TLE are not yet understood, which poses a challenge for the development of novel treatment strategies. Recently, we discovered that closed-loop optogenetic intervention (COI) can significantly curtail on-going electrographic and behavioral seizures in chronic experimental TLE with high spatial, temporal, and cell-type specificity, and that it can be used as a powerful, versatile research tool for hypothesis testing o understand TLE mechanisms. Here we propose to test the hypothesis that COI achieves long-term seizure control, as well as the amelioration of cognitive comorbidities and pathological functional network properties, during both the chronic and latent phases of TLE. The hypothesis will be tested in experimental mouse models of TLE, and the assessment will be carried out with electrophysiological and behavioral techniques as well as large-scale in vivo functional imaging methods in the CA1 region of the mouse hippocampus. It is anticipated that defining the functional consequences of COI in TLE will have a significant impact by advancing our understanding of the role of activity-dependent pathological processes in chronic epilepsy and epileptogenesis, and aid the future development of novel anti-epileptic treatment strategies.

Project Summary The 2017 Gordon Research Conference (GRC) on Inhibition in the Central Nervous System will be held at Les Diablerets Conference Center, Les Diablerets, Switzerland, on June 25-30, 2017. This international research conference has been held every 2 years since 2005 as part of the GRC conference series. It will be preceded on June 24-25, 2017, as in previous editions, by the Gordon Research Seminar (GRS), which is reserved for graduate students and postdocs in order to give them an introduction to the main topics of the GRC. Inhibition, mediated primarily by the neurotransmitter GABA, regulates all aspects of central nervous system (CNS) function and represents a major target for therapeutics. The scientific community working on inhibitory neurotransmission is broad and very dynamic. This GRC provides a major forum bringing together leaders in the field along with rising new stars among early-career investigators. The goal of this meeting is to increase our understanding of the molecular, synaptic and network mechanisms contributing to the critical role of inhibitory neurotransmission in normal and abnormal CNS function. To achieve this goal, the meeting will pursue specific aims that include dissemination of the latest discoveries about inhibition in brain function and dysfunction, promotion of diversity and collaboration within the field, and advancement of the training of graduate students and postdoctoral fellows. These aims will be met by convening 35 world-class speakers and 9 discussion leaders actively working in diverse areas of inhibition from eight different countries (21 from the US; 17 women), ensuring internationality and diversity. The GRC will accommodate up to 200 participants at a five-day conference in an isolated setting. The health relatedness of this application is that discussions at the Inhibition in the CNS GRC/GRS meetings will define the questions that require experimental resolution in areas related to cognition, human development, drug abuse, and a variety of neurological and psychiatric disorders that involve dysregulated inhibition including epilepsy, autism, schizophrenia and other diseases. Taken together, it is expected that the scientific discussions, research talks, poster sessions, and various informal interactions between the diverse participants of this conference will advance our understanding of fundamental mechanisms underlying in CNS function and human disease.

Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome in adults. Current treatment options for TLE are inadequate, as too many patients suffer from uncontrolled seizures and from negative side effects of treatment. Endogenous cannabinoid signaling has been recognized as a major, potent regulator of presynaptic neurotransmitter release in the brain, and there has been a recent surge of interest in using exogenous cannabinoid compounds obtained from the marijuana plant for the control of intractable epilepsy. However, mechanisms underlying cannabinoid control of neuronal excitability are not well understood. Recently, we discovered a fundamentally new, functionally significant, postsynaptic mechanism by which cannabinoids control excitability in hippocampal pyramidal cells. This pathway involves the potent, cannabinoid type 1 receptor- (CB1) mediated modulation of the h-current (Ih), a key regulator of dendritic excitability generated by hyperpolarization-activated, cyclic nucleotide-gated channels (HCNs). Here we propose to test the hypothesis that that medically relevant cannabinoids exert their anti-convulsant actions in chronic TLE partly through the regulation of Ih in principal cells and interneurons throughout the cortical mantle. The hypothesis will be tested in experimental mouse models of TLE, and the assessment will be carried out with in vitro and in vivo electrophysiology, cell-type-specific nanoscale super-resolution molecular imaging in specific subcellular profiles of identified pyramidal cells and interneurons at a high throughput, and data-driven supercomputational network modeling. We anticipate that defining the functional consequences of a novel cannabinoid regulator of neuronal excitability in chronic epilepsy will lead to significant advances in the understanding of disease mechanisms in chronic epilepsy, and will aid the development of cannabis-based anti-epileptic treatment strategies.

The Data Science Core, based at Stanford University, is the component through which the overall management and sharing of experimental and simulation data will be conducted. The Data Science Core will implement the Data Science Plan by developing an integrated software framework for data storage, analysis, and simulation, and by closely collaborating with all team members to ensure that their research needs are met in a timely manner. This effort will require a full-time data scientist that will be responsible for implementing and overseeing the data management framework and ensuring its effective use among team members. The data management framework, detailed in the data science plan, is based on a common description and storage format for experimental datasets produced by the proposed experiments in Projects 1-4, and will include adapted versions of the existing analysis software or new analysis tools that support the common format, software tools to efficiently extract and represent cellular and network properties from experimental time series, and a pipeline to use data stored in these formats to constrain our large-scale neuronal network models in Project 5. The principal data scientist will be responsible for collaboration with external organizations that develop scientific data formats, such as Neurodata Without Borders and the HDF Group, in order to ensure that best technical practices are followed in development of the storage format and support software, and for effective dissemination to the broader scientific community of all software and data generated by the projects via a resource such as Collaborative Research in Computational Neuroscience (CRCNS). The Data Science Core will play an important part in achieving the overall goals of the research projects by ensuring consistent use of analysis methods, facilitating data sharing among team members, allowing direct comparison of the outcomes of experiments performed in different labs under different conditions, and will accelerate the development of open-source software tools to help increase reproducibility across research teams.

Although neuroscience has provided a great deal of information about how neurons work, the fundamental question of how neurons function together in a network to produce cognition has been difficult to address. Our group has been at the forefront of developing methods that allow large scale monitoring of identified neurons, monitoring of voltage signals by optical means and elucidation of subcellular events in dendrites, all of which can now be done in awake behaving animals. We propose to use these methods to provide a deep understanding of how the neurons of the hippocampal region generate the sharp-wave ripple (SPW- R). This remarkable signal has been shown to depend on prior learning and to produce high-speed replay of memory sequences (e.g. a path along a track). The function of this signal is memory consolidation; disruption of SPW-Rs results in strong deficits in memory-guided behavior. Because much is known about the hippocampal cell types involved and their network connections, understanding the SPW-R is a tractable target for the first major effort to elucidate the cellular/network mechanism of a mammalian brain signal at an analytical level comparable to that achieved in the study of simple invertebrate systems. Project 1 is aimed at understanding the external and intra-hippocampal pathways that control the initiation of SPW-Rs. Project 2 deals with the events that occur during the SPW-R, including the timing of activity in identified cell types and understanding the fundamental network architecture by which memory sequences are produced. Project 3 deals with how the information that is replayed during the SPW-R is encoded. We will attempt to create an artificial memory and then determine whether the memory is replayed during a SPW-R; we will also interfere with molecular mechanisms of memory storage to determine whether we can erase the memories that are replayed during the SPW-R. Project 4 builds upon recent work indicating that differentially projecting CA1 pyramidal cells have distinct properties and will test the possibility that SPW- Rs in distinct output channels may carry different information and affect different behaviors. In Project 5 we will develop the first non-reduced computational model of the hippocampus, incorporating information about cell types and connections. This will be a major new resource for our group and the research community that will permit unprecedentedly close interplay between experiment and computation. To the extent that the model can account for the experimental observations, we can use it to understand underlying network principles and design interventional experiments to validate this understanding. To the extent that the model cannot explain results, it will help point us to aspects of network function that require further elucidation. Taken together, Projects 1-5 provide a tractable path to a major breakthrough in understanding how a cognitively important brain signal is generated.

There are 65 million people worldwide with epilepsy and 150,000 new cases of epilepsy are diagnosed in the US annually. However, treatment options for epilepsy remain inadequate, with many patients suffering from treatment-resistant seizures, cognitive comorbidities and the negative side effects of treatment. A major obstacle to progress towards the development of new therapies is the fact that preclinical epilepsy research typically requires labor-intensive and expensive 24/7 video-EEG monitoring of seizures that rests on the subjective scoring of seizure phenotypes by human observers (as exemplified by the widely used Racine scale of behavioral seizures). Recently, the Datta lab showed that complex animal behaviors are structured in stereotyped modules (?syllables?) at sub-second timescales and arranged according to specific rules (?grammar?). These syllables can be detected without observer bias using a method called motion sequencing (MoSeq) that employs video imaging with a 3D camera combined with artificial intelligence (AI)-assisted video analysis to characterize behavior. Through collaboration between the Soltesz and Datta labs, exciting data were obtained that demonstrated that MoSeq can be adapted for epilepsy research to perform objective, inexpensive and automated phenotyping of mice in a mouse model of chronic temporal lobe epilepsy. Here we propose to test and improve MoSeq further to address long-standing, fundamental challenges in epilepsy research. This includes the development of an objective alternative to the Racine scale, testing of MoSeq as an automated anti-epileptic drug (AED) screening method, and the development of human observer- independent behavioral biomarkers for seizures, epileptogenesis, and cognitive comorbidities. In addition, we plan to dramatically extend the epilepsy-related capabilities of MoSeq to include the automated tracking of finer-scale body parts (e.g., forelimb and facial clonus) that are not possible with the current approach. Finally, we propose to develop the analysis pipeline for MoSeq into a form that is intuitive, inexpensive, user-friendly and thus easily sharable with the research community. We anticipate that these results will have a potentially transformative effect on the field by demonstrating the feasibility and power of automated, objective, user- independent, inexpensive analysis of both acquired and genetic epilepsy phenotypes.

Temporal lobe epilepsy (TLE) is the most common epilepsy in adults, and it is frequently refractory to current anti-epileptic drugs, with treatments often exerting a variety of debilitating side effects. A major barrier for the development of novel treatment strategies is our insufficient understanding of the precise cellular and circuit mechanisms underlying TLE. A centrally important but unresolved question in TLE concerns the mechanisms underlying the excessive, dysregulated production of action potentials at the axon initial segment (AIS) of excitatory principal cells (PCs). Synaptic control of AIS is provided by a unique, evolutionarily conserved, GABAergic cell-type, the axo-axonic cells (AACs). AACs form synaptic contacts exclusively with the AIS of PCs, placing AACs in a strategic position to control action potential generation. However, due to technical limitations, our knowledge about the in vivo function and regulation of AACs in the normal and epileptic hippocampus has been extremely limited. Here we propose to employ a combination of recent technical breakthroughs to test hypotheses about the in vivo functional effects, activity dynamics and efficacy of AAC- mediated control of AIS in mouse models of chronic TLE. The planned project will also determine if it is possible to mitigate epilepsy-related pathologically hyperactive circuits and cognitive deficits through interventions selectively directed at the AAC-dependent, endogenous GABAergic processes regulating AIS in chronic epilepsy. The proposed project aims to fill a major knowledge gap and address long-standing controversies concerning the interneuronal regulation of AIS in epilepsy by leveraging expertise in novel large- scale, high-resolution in vivo functional imaging techniques in combination with advanced electrophysiological, behavioral, optogenetic and computational modeling techniques in the CA1 region of the mouse hippocampus. It is anticipated that defining the function, regulation and therapeutic potential of AACs in TLE will have a significant impact by advancing our understanding of key circuit control mechanisms in chronic epilepsy and aid the future development of novel anti-epileptic treatment strategies.