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• W2923443614 abstract "Current drug treatments for epilepsy attempt to broadly restrict excitability to mask a symptom, seizures, with little regard for the heterogeneous mechanisms that underlie disease manifestation across individuals. Here, we discuss the need for a more complete view of epilepsy, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG). We highlight how major advances in neuroscience tool development now enable multi-scale investigation of fundamental questions to resolve the currently controversial understanding of seizure networks. These findings will provide essential insight into what has emerged as a disconnect between the different levels of investigation and identify new targets and treatment options. Current drug treatments for epilepsy attempt to broadly restrict excitability to mask a symptom, seizures, with little regard for the heterogeneous mechanisms that underlie disease manifestation across individuals. Here, we discuss the need for a more complete view of epilepsy, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG). We highlight how major advances in neuroscience tool development now enable multi-scale investigation of fundamental questions to resolve the currently controversial understanding of seizure networks. These findings will provide essential insight into what has emerged as a disconnect between the different levels of investigation and identify new targets and treatment options. Epilepsy affects 1 in 26 people in their lifetime (Hesdorffer et al., 2011aHesdorffer D.C. Logroscino G. Benn E.K.T. Katri N. Cascino G. Hauser W.A. Estimating risk for developing epilepsy: a population-based study in Rochester, Minnesota.Neurology. 2011; 76: 23-27Crossref PubMed Scopus (126) Google Scholar) and is characterized by the predisposition to generate seizures (Fisher et al., 2014Fisher R.S. Acevedo C. Arzimanoglou A. Bogacz A. Cross J.H. Elger C.E. Engel Jr., J. Forsgren L. French J.A. Glynn M. et al.ILAE official report: a practical clinical definition of epilepsy.Epilepsia. 2014; 55: 475-482Crossref PubMed Scopus (1177) Google Scholar). Despite continuous development of new anti-seizure medications, seizures are inadequately controlled in 30%–40% of cases, a situation that has seemingly not improved since the 1800s (Löscher and Schmidt, 2011Löscher W. Schmidt D. Modern antiepileptic drug development has failed to deliver: ways out of the current dilemma.Epilepsia. 2011; 52: 657-678Crossref PubMed Scopus (287) Google Scholar). This is troubling because epilepsy can be associated with a 27 times greater risk of sudden death than the general population (Holst et al., 2013Holst A.G. Winkel B.G. Risgaard B. Nielsen J.B. Rasmussen P.V. Haunsø S. Sabers A. Uldall P. Tfelt-Hansen J. Epilepsy and risk of death and sudden unexpected death in the young: a nationwide study.Epilepsia. 2013; 54: 1613-1620Crossref PubMed Scopus (63) Google Scholar). Furthermore, epilepsy is often accompanied by cognitive, behavioral, and psychiatric comorbidities that reduce quality of life (Kanner, 2016Kanner A.M. Management of psychiatric and neurological comorbidities in epilepsy.Nat. Rev. Neurol. 2016; 12: 106-116Crossref PubMed Scopus (92) Google Scholar). Seizure frequency plays a central role in the negative aspects of epilepsy and emphasizes the utmost importance for therapies that prevent seizures. When possible, surgical intervention remains the best option for refractory epilepsy (Jette et al., 2014Jette N. Reid A.Y. Wiebe S. Surgical management of epilepsy.CMAJ. 2014; 186: 997-1004Crossref PubMed Scopus (0) Google Scholar), though less invasive strategies should remain a goal (Krook-Magnuson and Soltesz, 2015Krook-Magnuson E. Soltesz I. Beyond the hammer and the scalpel: selective circuit control for the epilepsies.Nat. Neurosci. 2015; 18: 331-338Crossref PubMed Scopus (46) Google Scholar). Successful surgical outcomes depend on proper characterization of the seizure-generating network. Accordingly, mapping and understanding seizure networks remains a major focus of contemporary epilepsy research at basic and clinical levels, but the current understanding is largely based on a macroscopic scale that is too far removed from the microscale cell-to-cell communication that generates and supports seizures. It is sobering that “the rationale of temporal epilepsy surgery remains opaque or even contradictory,” even in cases where there is a lesion or abnormality visible in brain-imaging scans (Cleveland Clinic, 2017Cleveland ClinicThe Sixth Annual Brain Mapping Workshop: SEEG and the hippocampus.https://www.himssinnovationcenter.org/sixth-annual-brain-mapping-workshop-seeg-and-hippocampusDate: 2017Google Scholar). This lack of confidence is exacerbated by the obscurity of linking electrographic recordings of seizures with the role of the local network in seizure activity. However, recent work highlighted in this review has begun to uncover the cellular ensembles that are responsible for the macroscopic electrographic properties of seizures and are refining our understanding of seizure networks. Here, we discuss evidence that changes at the microscopic level, corresponding to the functional arrangement of specific cell types within microcircuits, are a critical source of differences in macroscopic epilepsy expression. Conversely, ostensibly similar epilepsy expression at the macroscopic scale can originate from a variety of mechanisms at the microscopic scale. Thus, a detailed understanding of seizure mechanisms at the microscale, encompassing cellular signaling and communication, is necessary to explain epilepsy expression at the macroscale, including seizure behavior, electroencephalography (EEG) patterns, and neuroimaging findings. These microscale changes have a significant impact on the closely related, imperative outstanding question of how seizures generalize. In other words, what mechanisms underlie the ability of some seizures to spread beyond the brain region(s) of origin to cause behavioral convulsions (tonic-clonic activity)? Because generalized tonic-clonic seizures (GTCSs) preceded all cases of witnessed sudden unexpected death in epilepsy (SUDEP) (Ryvlin et al., 2013Ryvlin P. Nashef L. Lhatoo S.D. Bateman L.M. Bird J. Bleasel A. Boon P. Crespel A. Dworetzky B.A. Høgenhaven H. et al.Incidence and mechanisms of cardiorespiratory arrests in epilepsy monitoring units (MORTEMUS): a retrospective study.Lancet Neurol. 2013; 12: 966-977Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar) and frequency of GTCSs is the greatest risk factor for SUDEP (Hesdorffer et al., 2011bHesdorffer D.C. Tomson T. Benn E. Sander J.W. Nilsson L. Langan Y. Walczak T.S. Beghi E. Brodie M.J. Hauser A. ILAE Commission on Epidemiology; Subcommission on MortalityCombined analysis of risk factors for SUDEP.Epilepsia. 2011; 52: 1150-1159Crossref PubMed Scopus (237) Google Scholar), answering this question remains critical. Finally, we highlight how modern neuroscience recording techniques that are genetically targeted can be used to address basic science questions and validate clinical methodologies. Using these methods to resolve the underlying differences between macroscopically similar electrographic events is crucially informative to how seizures are conceptualized. Together, these insights will provide a more complete understanding of seizures to refine current therapies and develop novel treatments. Although particular brain regions, such as the hippocampus, are often responsible for seizures, it is unclear how specific microcircuit elements, the non-uniform functional arrangement of cells within a brain region, are implicated across individuals with seizures originating from the same structure. Resolving these microscopic differences is critical to understanding and treating epilepsy (for insights from genetic epilepsies, see Box 1), especially when divergent epilepsies at the microscale are grossly classified as the same epilepsy (e.g., temporal lobe epilepsy [TLE]) because they involve the same brain region. One prime example is the pyramidal cell population in the CA1 region of the hippocampus (Figure 1A). Although CA1 has long been known to be the primary output node of the hippocampus, emerging data from the last decade have shown that there are robust differences among the principle cell population, which can be divided into deep or superficial groups along the radial axis of CA1 (reviewed by Soltesz and Losonczy, 2018Soltesz I. Losonczy A. CA1 pyramidal cell diversity enabling parallel information processing in the hippocampus.Nat. Neurosci. 2018; 21: 484-493Crossref PubMed Scopus (8) Google Scholar). Differences between deep and superficial CA1 neurons have been described for gene expression, morphology, and the local and long-range connections coming to and from principal cells (Bannister and Larkman, 1995Bannister N.J. Larkman A.U. Dendritic morphology of CA1 pyramidal neurones from the rat hippocampus: II. Spine distributions.J. Comp. Neurol. 1995; 360: 161-171Crossref PubMed Scopus (94) Google Scholar, Cembrowski et al., 2016Cembrowski M.S. Bachman J.L. Wang L. Sugino K. Shields B.C. Spruston N. Spatial gene-expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons.Neuron. 2016; 89: 351-368Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar, Jarsky et al., 2008Jarsky T. Mady R. Kennedy B. Spruston N. Distribution of bursting neurons in the CA1 region and the subiculum of the rat hippocampus.J. Comp. Neurol. 2008; 506: 535-547Crossref PubMed Scopus (62) Google Scholar, Lee et al., 2014Lee S.H. Marchionni I. Bezaire M. Varga C. Danielson N. Lovett-Barron M. Losonczy A. Soltesz I. Parvalbumin-positive basket cells differentiate among hippocampal pyramidal cells.Neuron. 2014; 82: 1129-1144Abstract Full Text Full Text PDF PubMed Scopus (117) Google Scholar). Although the structure of CA1 cells is not classically thought to be arranged in a layered architecture as seen in cortex (except under genetic mutations that cause abnormal migration; see Jiang et al., 2016Jiang Y. Gavrilovici C. Chansard M. Liu R.H. Kiroski I. Parsons K. Park S.K. Teskey G.C. Rho J.M. Nguyen M.D. Ndel1 and Reelin maintain postnatal CA1 hippocampus integrity.J. Neurosci. 2016; 36: 6538-6552Crossref PubMed Scopus (3) Google Scholar), these findings show that clear differences exist among the same cell types within a region. When also considering the division of pyramidal cell function along the dorsal-to-ventral and medial-to-lateral axis of the hippocampus (Igarashi et al., 2014Igarashi K.M. Ito H.T. Moser E.I. Moser M.B. Functional diversity along the transverse axis of hippocampal area CA1.FEBS Lett. 2014; 588: 2470-2476Crossref PubMed Google Scholar, Cembrowski et al., 2018Cembrowski M.S. Phillips M.G. DiLisio S.F. Shields B.C. Winnubst J. Chandrashekar J. Bas E. Spruston N. Dissociable structural and functional hippocampal outputs via distinct subiculum cell classes.Cell. 2018; 173: 1280-1292.e18Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar), a macroscopic view of a cell layer is blind to these parallel pathways that are functionally distinct.Box 1Genetic Epilepsies: Variability in Epilepsy Manifestation Across Scales Despite a Mutation Occurring in All CellsThe advent of modern sequencing technologies, such as whole-genome exome sequencing, has increased the number of epilepsy patients undergoing genetic testing and added to the growing list of epilepsy-associated genes (Helbig et al., 2016Helbig K.L. Farwell Hagman K.D. Shinde D.N. Mroske C. Powis Z. Li S. Tang S. Helbig I. Diagnostic exome sequencing provides a molecular diagnosis for a significant proportion of patients with epilepsy.Genet. Med. 2016; 18: 898-905Abstract Full Text Full Text PDF PubMed Scopus (122) Google Scholar). Despite such mutations being present in every cell at the macroscale, expression of mutations can vary across the scale of brain regions, cell types, and synapses to result in or modulate epilepsy manifestation, as illustrated by the prominent examples of epilepsy-related gene mutations below.Brain Regions. Different epilepsy phenotypes are exhibited by knockout of either the Kv1.1 or 1.2 subunits, which belong to the same family of voltage-gated potassium channels. Although Kv1.1 knockouts display symptoms emblematic of limbic dysfunction, Kv1.2 knockouts display symptoms more associated with changes to brainstem and subcortical structures (Robbins and Tempel, 2012Robbins C.A. Tempel B.L. Kv1.1 and Kv1.2: similar channels, different seizure models.Epilepsia. 2012; 53: 134-141Crossref PubMed Scopus (0) Google Scholar). It is thought that differences in the expression of these channels underlie the distinct epilepsy phenotypes, with Kv1.1 having greater expression in hippocampus than Kv1.2 (Prüss et al., 2010Prüss H. Grosse G. Brunk I. Veh R.W. Ahnert-Hilger G. Age-dependent axonal expression of potassium channel proteins during development in mouse hippocampus.Histochem. Cell Biol. 2010; 133: 301-312Crossref PubMed Scopus (19) Google Scholar, Wang et al., 1994Wang H. Kunkel D.D. Schwartzkroin P.A. Tempel B.L. Localization of Kv1.1 and Kv1.2, two K channel proteins, to synaptic terminals, somata, and dendrites in the mouse brain.J. Neurosci. 1994; 14: 4588-4599Crossref PubMed Google Scholar).Cell Types. One of the strongest associations between a particular gene and epilepsy is Scn1a, encoding the sodium channel Nav1.1, and Dravet syndrome (Catterall et al., 2010Catterall W.A. Kalume F. Oakley J.C. NaV1.1 channels and epilepsy.J. Physiol. 2010; 588: 1849-1859Crossref PubMed Scopus (200) Google Scholar, Oliva et al., 2012Oliva M. Berkovic S.F. Petrou S. Sodium channels and the neurobiology of epilepsy.Epilepsia. 2012; 53: 1849-1859Crossref PubMed Scopus (75) Google Scholar). About 70%–90% of patients with Dravet have nonsense mutations in Scn1a, leading to a non-functional protein (Escayg and Goldin, 2010Escayg A. Goldin A.L. Sodium channel SCN1A and epilepsy: mutations and mechanisms.Epilepsia. 2010; 51: 1650-1658Crossref PubMed Scopus (178) Google Scholar). Loss-of-function studies in mouse models have found a reduction in sodium currents specifically in GABAergic interneurons and not excitatory neurons early on, possibly due to higher expression of the channel in these cell types (Yu et al., 2006Yu F.H. Mantegazza M. Westenbroek R.E. Robbins C.A. Kalume F. Burton K.A. Spain W.J. McKnight G.S. Scheuer T. Catterall W.A. Reduced sodium current in GABAergic interneurons in a mouse model of severe myoclonic epilepsy in infancy.Nat. Neurosci. 2006; 9: 1142-1149Crossref PubMed Scopus (562) Google Scholar, Ogiwara et al., 2007Ogiwara I. Miyamoto H. Morita N. Atapour N. Mazaki E. Inoue I. Takeuchi T. Itohara S. Yanagawa Y. Obata K. et al.Nav1.1 localizes to axons of parvalbumin-positive inhibitory interneurons: a circuit basis for epileptic seizures in mice carrying an Scn1a gene mutation.J. Neurosci. 2007; 27: 5903-5914Crossref PubMed Scopus (429) Google Scholar).Synapses. Mutations in genes for subunits of the GABAA receptor (GABAAR), a heteropentameric ion channel mediating the majority of inhibitory transmission in the brain (Sieghart, 2006Sieghart W. Structure, pharmacology, and function of GABAA receptor subtypes.Adv. Pharmacol. 2006; 54: 231-263Crossref PubMed Scopus (212) Google Scholar, Simon et al., 2004Simon J. Wakimoto H. Fujita N. Lalande M. Barnard E.A. Analysis of the set of GABA(A) receptor genes in the human genome.J. Biol. Chem. 2004; 279: 41422-41435Crossref PubMed Scopus (166) Google Scholar), have been associated with a range of epilepsy syndromes (Oyrer et al., 2018Oyrer J. Maljevic S. Scheffer I.E. Berkovic S.F. Petrou S. Reid C.A. Ion channels in genetic epilepsy: from genes and mechanisms to disease-targeted therapies.Pharmacol. Rev. 2018; 70: 142-173Crossref PubMed Scopus (21) Google Scholar). Receptors with particular subunit compositions can preferentially localize and function at specific synapses, showing how dysfunction in certain GABAAR subunits can have circuit-specific effects. This is exemplified by the enrichment of α1 subunit containing GABAARs at synapses between parvalbumin (PV)-positive, perisomatic-targeting, fast-spiking interneurons and their granule cell targets in the dentate gyrus located close versus further away (Strüber et al., 2015Strüber M. Jonas P. Bartos M. Strength and duration of perisomatic GABAergic inhibition depend on distance between synaptically connected cells.Proc. Natl. Acad. Sci. USA. 2015; 112: 1220-1225Crossref PubMed Scopus (0) Google Scholar). Similar synapse-specific targeting of GABAARs has also been found between connections from different interneuron types onto CA1 pyramidal cells, with synapses from PV-expressing inputs functionally relying more on β3-containing GABAARs compared to those from somatostatin (SST)-expressing inputs (Nguyen and Nicoll, 2018Nguyen Q.A. Nicoll R.A. The GABAA receptor β subunit is required for inhibitory transmission.Neuron. 2018; 98: 718-725.e3Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar). These findings show how molecular components have a critical and specific impact on defining the circuit organization of the brain. The advent of modern sequencing technologies, such as whole-genome exome sequencing, has increased the number of epilepsy patients undergoing genetic testing and added to the growing list of epilepsy-associated genes (Helbig et al., 2016Helbig K.L. Farwell Hagman K.D. Shinde D.N. Mroske C. Powis Z. Li S. Tang S. Helbig I. Diagnostic exome sequencing provides a molecular diagnosis for a significant proportion of patients with epilepsy.Genet. Med. 2016; 18: 898-905Abstract Full Text Full Text PDF PubMed Scopus (122) Google Scholar). Despite such mutations being present in every cell at the macroscale, expression of mutations can vary across the scale of brain regions, cell types, and synapses to result in or modulate epilepsy manifestation, as illustrated by the prominent examples of epilepsy-related gene mutations below.Brain Regions. Different epilepsy phenotypes are exhibited by knockout of either the Kv1.1 or 1.2 subunits, which belong to the same family of voltage-gated potassium channels. Although Kv1.1 knockouts display symptoms emblematic of limbic dysfunction, Kv1.2 knockouts display symptoms more associated with changes to brainstem and subcortical structures (Robbins and Tempel, 2012Robbins C.A. Tempel B.L. Kv1.1 and Kv1.2: similar channels, different seizure models.Epilepsia. 2012; 53: 134-141Crossref PubMed Scopus (0) Google Scholar). It is thought that differences in the expression of these channels underlie the distinct epilepsy phenotypes, with Kv1.1 having greater expression in hippocampus than Kv1.2 (Prüss et al., 2010Prüss H. Grosse G. Brunk I. Veh R.W. Ahnert-Hilger G. Age-dependent axonal expression of potassium channel proteins during development in mouse hippocampus.Histochem. Cell Biol. 2010; 133: 301-312Crossref PubMed Scopus (19) Google Scholar, Wang et al., 1994Wang H. Kunkel D.D. Schwartzkroin P.A. Tempel B.L. Localization of Kv1.1 and Kv1.2, two K channel proteins, to synaptic terminals, somata, and dendrites in the mouse brain.J. Neurosci. 1994; 14: 4588-4599Crossref PubMed Google Scholar).Cell Types. One of the strongest associations between a particular gene and epilepsy is Scn1a, encoding the sodium channel Nav1.1, and Dravet syndrome (Catterall et al., 2010Catterall W.A. Kalume F. Oakley J.C. NaV1.1 channels and epilepsy.J. Physiol. 2010; 588: 1849-1859Crossref PubMed Scopus (200) Google Scholar, Oliva et al., 2012Oliva M. Berkovic S.F. Petrou S. Sodium channels and the neurobiology of epilepsy.Epilepsia. 2012; 53: 1849-1859Crossref PubMed Scopus (75) Google Scholar). About 70%–90% of patients with Dravet have nonsense mutations in Scn1a, leading to a non-functional protein (Escayg and Goldin, 2010Escayg A. Goldin A.L. Sodium channel SCN1A and epilepsy: mutations and mechanisms.Epilepsia. 2010; 51: 1650-1658Crossref PubMed Scopus (178) Google Scholar). Loss-of-function studies in mouse models have found a reduction in sodium currents specifically in GABAergic interneurons and not excitatory neurons early on, possibly due to higher expression of the channel in these cell types (Yu et al., 2006Yu F.H. Mantegazza M. Westenbroek R.E. Robbins C.A. Kalume F. Burton K.A. Spain W.J. McKnight G.S. Scheuer T. Catterall W.A. Reduced sodium current in GABAergic interneurons in a mouse model of severe myoclonic epilepsy in infancy.Nat. Neurosci. 2006; 9: 1142-1149Crossref PubMed Scopus (562) Google Scholar, Ogiwara et al., 2007Ogiwara I. Miyamoto H. Morita N. Atapour N. Mazaki E. Inoue I. Takeuchi T. Itohara S. Yanagawa Y. Obata K. et al.Nav1.1 localizes to axons of parvalbumin-positive inhibitory interneurons: a circuit basis for epileptic seizures in mice carrying an Scn1a gene mutation.J. Neurosci. 2007; 27: 5903-5914Crossref PubMed Scopus (429) Google Scholar).Synapses. Mutations in genes for subunits of the GABAA receptor (GABAAR), a heteropentameric ion channel mediating the majority of inhibitory transmission in the brain (Sieghart, 2006Sieghart W. Structure, pharmacology, and function of GABAA receptor subtypes.Adv. Pharmacol. 2006; 54: 231-263Crossref PubMed Scopus (212) Google Scholar, Simon et al., 2004Simon J. Wakimoto H. Fujita N. Lalande M. Barnard E.A. Analysis of the set of GABA(A) receptor genes in the human genome.J. Biol. Chem. 2004; 279: 41422-41435Crossref PubMed Scopus (166) Google Scholar), have been associated with a range of epilepsy syndromes (Oyrer et al., 2018Oyrer J. Maljevic S. Scheffer I.E. Berkovic S.F. Petrou S. Reid C.A. Ion channels in genetic epilepsy: from genes and mechanisms to disease-targeted therapies.Pharmacol. Rev. 2018; 70: 142-173Crossref PubMed Scopus (21) Google Scholar). Receptors with particular subunit compositions can preferentially localize and function at specific synapses, showing how dysfunction in certain GABAAR subunits can have circuit-specific effects. This is exemplified by the enrichment of α1 subunit containing GABAARs at synapses between parvalbumin (PV)-positive, perisomatic-targeting, fast-spiking interneurons and their granule cell targets in the dentate gyrus located close versus further away (Strüber et al., 2015Strüber M. Jonas P. Bartos M. Strength and duration of perisomatic GABAergic inhibition depend on distance between synaptically connected cells.Proc. Natl. Acad. Sci. USA. 2015; 112: 1220-1225Crossref PubMed Scopus (0) Google Scholar). Similar synapse-specific targeting of GABAARs has also been found between connections from different interneuron types onto CA1 pyramidal cells, with synapses from PV-expressing inputs functionally relying more on β3-containing GABAARs compared to those from somatostatin (SST)-expressing inputs (Nguyen and Nicoll, 2018Nguyen Q.A. Nicoll R.A. The GABAA receptor β subunit is required for inhibitory transmission.Neuron. 2018; 98: 718-725.e3Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar). These findings show how molecular components have a critical and specific impact on defining the circuit organization of the brain. The segregation of function within hippocampal cell layers could have important implications for seizures and epilepsy (Figure 1). For example, it is unknown whether seizures preferentially recruit deep or superficial cell layers. Given the divergent outputs of these cell types, this organization will undoubtedly influence where seizures spread and could vary within and between patients. Axonal sprouting between otherwise distinct cell groups could also disrupt the normally distinct parallel processing and contribute to excitability and interictal (between seizures) cognitive and behavioral comorbidities. Moreover, macroscopic cell loss of CA1 should be sub-characterized by the differential loss of deep versus superficial neurons (Towfighi et al., 2004Towfighi J. Housman C. Brucklacher R. Vannucci R.C. Neuropathology of seizures in the immature rabbit.Brain Res. Dev. Brain Res. 2004; 152: 143-152Crossref PubMed Scopus (0) Google Scholar), which could vary widely among patients and be a source of variation in epilepsy expression. The implications of heterogeneity within microcircuits extend to other brain areas, where these characteristics are beginning to be understood rather than being an exception of CA1 (Krook-Magnuson et al., 2012Krook-Magnuson E. Varga C. Lee S.H. Soltesz I. New dimensions of interneuronal specialization unmasked by principal cell heterogeneity.Trends Neurosci. 2012; 35: 175-184Abstract Full Text Full Text PDF PubMed Scopus (43) Google Scholar, Varga et al., 2010Varga C. Lee S.Y. Soltesz I. Target-selective GABAergic control of entorhinal cortex output.Nat. Neurosci. 2010; 13: 822-824Crossref PubMed Scopus (109) Google Scholar, Hunt et al., 2018Hunt D.L. Linaro D. Si B. Romani S. Spruston N. A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus.Nat. Neurosci. 2018; 21: 985-995Crossref PubMed Scopus (2) Google Scholar). Because this connectivity bias is preserved in chronically epileptic animal models (Armstrong et al., 2016Armstrong C. Wang J. Yeun Lee S. Broderick J. Bezaire M.J. Lee S.H. Soltesz I. Target-selectivity of parvalbumin-positive interneurons in layer II of medial entorhinal cortex in normal and epileptic animals.Hippocampus. 2016; 26: 779-793Crossref PubMed Scopus (15) Google Scholar), determining how seizures and interictal abnormalities are expressed within heterogeneous microcircuits is a valid concern. The implications of parallel pathways within the same microcircuit are significant in the context of the differences between observed epilepsy mechanisms at the macro- versus microscale. A basic assumption of epileptiform activity is that it is due to recurrent and hypersynchronous runaway excitation across multiple scales. This tenet arose from looking at neuronal activity at a population level (i.e., EEG). Closer examination, however, highlights that neuronal activity during seizures and epileptiform events are highly heterogeneous. Neuronal activation patterns observed from in vitro slice models of interictal spikes display spatially clustered arrangements of groups of neurons that vary between individual spikes, despite electrographically similar events (Feldt Muldoon et al., 2013Feldt Muldoon S. Soltesz I. Cossart R. Spatially clustered neuronal assemblies comprise the microstructure of synchrony in chronically epileptic networks.Proc. Natl. Acad. Sci. USA. 2013; 110: 3567-3572Crossref PubMed Scopus (70) Google Scholar, Sabolek et al., 2012Sabolek H.R. Swiercz W.B. Lillis K.P. Cash S.S. Huberfeld G. Zhao G. Ste Marie L. Clemenceau S. Barsh G. Miles R. Staley K.J. A candidate mechanism underlying the variance of interictal spike propagation.J. Neurosci. 2012; 32: 3009-3021Crossref PubMed Scopus (0) Google Scholar). Similar analysis based on single-unit recordings has also been performed on patients undergoing epilepsy monitoring and revealed heterogeneous spiking outside of the seizure focus within a given seizure but consistent spiking patterns between seizures (Truccolo et al., 2011Truccolo W. Donoghue J.A. Hochberg L.R. Eskandar E.N. Madsen J.R. Anderson W.S. Brown E.N. Halgren E. Cash S.S. Single-neuron dynamics in human focal epilepsy.Nat. Neurosci. 2011; 14: 635-641Crossref PubMed Scopus (258) Google Scholar). These findings highlight the inadequacy of population-level measures, such as EEG, and the need to characterize microscale changes to potentially explain differences in epilepsy phenotypes, manifestations, and possibly treatment options (Figure 1B). The advent of molecular tools for functional analysis of specific circuits has enabled researchers to test the contribution of specific microcircuit elements to macroscopic seizure expression, most commonly EEG recordings and behavioral presentation. Optogenetics enables researchers to use light to control the activity of a genetically defined cell population with spatiotemporal precision (Zemelman et al., 2002Zemelman B.V. Lee G.A. Ng M. Miesenböck G. Selective photostimulation of genetically chARGed neurons.Neuron. 2002; 33: 15-22Abstract Full Text Full Text PDF PubMed Scopus (289) Google Scholar, Li et al., 2005Li X. Gutierrez D.V. Hanson M.G. Han J. Mark M.D. Chiel H. Hegemann P. Landmesser L.T. Herlitze S. Fast noninvasive activation and inhibition of neural and network activity by vertebrate rhodopsin and green algae channelrhodopsin.Proc. Natl. Acad. Sci. USA. 2005; 102: 17816-17821Crossref PubMed Scopus (342) Google Scholar, Boyden et al., 2005Boyden E.S. Zhang F. Bamberg E. Nagel G. Deisseroth K. Millisecond-timescale, genetically targeted optical control of neural activity.Nat. Neurosci. 2005; 8: 1263-1268Crossref PubMed Scopus (2416) Google Scholar) and is a powerful tool for controlling seizures (recent reviews by Choy et al., 2017Choy M. Duffy B.A. Lee J.H. Optogenetic study of networks in epilepsy.J. Neurosci. Res. 2017; 95: 2325-2335Crossref PubMed Scopus (8) Google Scholar and Bui et al., 2017Bui A.D. Alexander A. Soltesz I. Seizing control: from current treatments to optogenetic interventions in epilepsy.Neuroscientist. 2017; 23: 68-81Crossref PubMed Scopus (2) Google Scholar). One application of optogenetics is to increase or decrease the activity of a cell type of interest in a closed-loop manner such that control only occurs when seizures are detected. Ideally, this method could be used to identify critical nodes in a seizure network and to test the involvement of specific asp" @default.
• W2923443614 created "2019-04-01" @default.
• W2923443614 creator A5054396178 @default.
• W2923443614 creator A5054420671 @default.
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• W2923443614 date "2019-03-01" @default.
• W2923443614 modified "2023-10-16" @default.
• W2923443614 title "Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks" @default.
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