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Neural systems are organized in a modular way, serving multiple functionalities. This multiplicity requires that both positive (e.g. excitatory, phase-coherent) and negative (e.g. inhibitory, phase-opposing) interactions take place across brain modules. Unfortunately, most methods to detect modules from time series either neglect or convert to positive, any measured negative correlation. This may leave a significant part of the sign-dependent functional structure undetected. Here we present a novel method, based on random matrix theory, for the identification of sign-dependent modules in the brain. Our method filters out both local (unit-specific) noise and global (system-wide) dependencies that typically obfuscate the presence of such structure. The method is guaranteed to identify an optimally contrasted functional ‘signature’, i.e. a partition into modules that are positively correlated internally and negatively correlated across. The method is purely data-driven, does not use any arbitrary threshold or network projection, and outputs only statistically significant structure. In measurements of neuronal gene expression in the biological clock of mice, the method systematically uncovers two otherwise undetectable, negatively correlated modules whose relative size and mutual interaction strength are found to depend on photoperiod. [ABSTRACT FROM AUTHOR]

Information transmission in the human brain is a fundamentally dynamic network process. In partial epilepsy, this process is perturbed and highly synchronous seizures originate in a local network, the so-called epileptogenic zone (EZ), before recruiting other close or distant brain regions. We studied patient-specific brain network models of 15 drug-resistant epilepsy patients with implanted stereotactic electroencephalography (SEEG) electrodes. Each personalized brain model was derived from structural data of magnetic resonance imaging (MRI) and diffusion tensor weighted imaging (DTI), comprising 88 nodes equipped with region specific neural mass models capable of demonstrating a range of epileptiform discharges. Each patient’s virtual brain was further personalized through the integration of the clinically hypothesized EZ. Subsequent simulations and connectivity modulations were performed and uncovered a finite repertoire of seizure propagation patterns. Across patients, we found that (i) patient-specific network connectivity is predictive for the subsequent seizure propagation pattern; (ii) seizure propagation is characterized by a systematic sequence of brain states; (iii) propagation can be controlled by an optimal intervention on the connectivity matrix; (iv) the degree of invasiveness can be significantly reduced via the proposed seizure control as compared to traditional resective surgery. To stop seizures, neurosurgeons typically resect the EZ completely. We showed that stability analysis of the network dynamics, employing structural and dynamical information, estimates reliably the spatiotemporal properties of seizure propagation. This suggests novel less invasive paradigms of surgical interventions to treat and manage partial epilepsy. [ABSTRACT FROM AUTHOR]

Quantification of interictal spikes in EEG may provide insight on epilepsy disease burden, but manual quantification of spikes is time-consuming and subject to bias. We present a probability-based, automated method for the classification and quantification of interictal events, using EEG data from kainate- and saline-injected mice (C57BL/6J background) several weeks post-treatment. We first detected high-amplitude events, then projected event waveforms into Principal Components space and identified clusters of spike morphologies using a Gaussian Mixture Model. We calculated the odds-ratio of events from kainate- versus saline-treated mice within each cluster, converted these values to probability scores, P(kainate), and calculated an Hourly Epilepsy Index for each animal by summing the probabilities for events where the cluster P(kainate) > 0.5 and dividing the resultant sum by the record duration. This Index is predictive of whether an animal received an epileptogenic treatment (i.e., kainate), even if a seizure was never observed. We applied this method to an out-of-sample dataset to assess epileptiform spike morphologies in five kainate mice monitored for ~1 month. The magnitude of the Index increased over time in a subset of animals and revealed changes in the prevalence of epileptiform (P(kainate) > 0.5) spike morphologies. Importantly, in both data sets, animals that had electrographic seizures also had a high Index. This analysis is fast, unbiased, and provides information regarding the salience of spike morphologies for disease progression. Future refinement will allow a better understanding of the definition of interictal spikes in quantitative and unambiguous terms. [ABSTRACT FROM AUTHOR]

Two-pore domain potassium channels (K2P) constitute major candidates for the regulation of background potassium currents in mammalian cells. Channels of the TREK subfamily are also well positioned to play an important role in sensory transduction due to their sensitivity to a large number of physiological and physical stimuli (pH, mechanical, temperature). Following our previous report describing the molecular expression of different K2P channels in the vagal sensory system, here we confirm that TREK channels are functionally expressed in neurons from the mouse nodose ganglion (mNG). Neurons were subdivided into three groups (A, Ah and C) based on their response to tetrodotoxin and capsaicin. Application of the TREK subfamily activator riluzole to isolated mNG neurons evoked a concentration-dependent outward current in the majority of cells from all the three subtypes studied. Riluzole increased membrane conductance and hyperpolarized the membrane potential by approximately 10 mV when applied to resting neurons. The resting potential was similar in all three groups, but C cells were clearly less excitable and showed smaller hyperpolarization-activated currents at -100 mV and smaller sustained currents at -30 mV. Our results indicate that the TREK subfamily of K2P channels might play an important role in the maintenance of the resting membrane potential in sensory neurons of the autonomic nervous system, suggesting its participation in the modulation of vagal reflexes. [ABSTRACT FROM AUTHOR]

Epileptic seizures are known to follow specific changes in brain dynamics. While some algorithms can nowadays robustly detect these changes, a clear understanding of the mechanism by which these alterations occur and generate seizures is still lacking. Here, we provide crossvalidated evidence that such changes are initiated by an alteration of physiological network state dynamics. Specifically, our analysis of long intracranial electroencephalography (iEEG) recordings from a group of 10 patients identifies a critical phase of a few hours in which time-dependent network states become less variable ("degenerate"), and this phase is followed by a global functional connectivity reduction before seizure onset. This critical phase is characterized by an abnormal occurrence of highly correlated network instances and is shown to be particularly associated with the activity of the resected regions in patients with validated postsurgical outcome. Our approach characterizes preseizure network dynamics as a cascade of 2 sequential events providing new insights into seizure prediction and control. [ABSTRACT FROM AUTHOR]

Seizure clustering is a common and significant phenomenon in patients with epilepsy. The clustering of spontaneous recurrent seizures (SRSs) in animal models of epilepsy, including mouse pilocarpine models, has been reported. However, most studies have analyzed seizures for a short duration after the induction of status epilepticus (SE). In this study, we investigated the detailed characteristics of seizure clustering in the chronic stage of a mouse pilocarpine-induced epilepsy model for an extended duration by continuous 24/7 video-EEG monitoring. A seizure cluster was defined as the occurrence of one or more seizures per day for at least three consecutive days and at least five seizures during the cluster period. We analyzed the cluster duration, seizure-free period, cluster interval, and numbers of seizures within and outside the seizure clusters. The video-EEG monitoring began 84.5±33.7 days after the induction of SE and continued for 53.7±20.4 days. Every mouse displayed seizure clusters, and 97.0% of the seizures occurred within a cluster period. The seizure clusters were followed by long seizure-free periods of 16.3±6.8 days, showing a cyclic pattern. The SRSs also occurred in a grouped pattern within a day. We demonstrate that almost all seizures occur in clusters with a cyclic pattern in the chronic stage of a mouse pilocarpine-induced epilepsy model. The seizure-free periods between clusters were long. These findings should be considered when performing in vivo studies using this animal model. Furthermore, this model might be appropriate for studying the unrevealed mechanism of ictogenesis. [ABSTRACT FROM AUTHOR]

Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhythms in health and disease. The dynamics of these models is dependent upon the choice of parameters, and therefore it is crucial to be able to understand how dynamics change when parameters are varied. Despite being considered low dimensional in comparison to micro-scale, neuronal network models, with regards to understanding the relationship between parameters and dynamics, NMMs are still prohibitively high dimensional for classical approaches such as numerical continuation. Therefore, we need alternative methods to characterise dynamics of NMMs in high dimensional parameter spaces. Here, we introduce a statistical framework that enables the efficient exploration of the relationship between model parameters and selected features of the simulated, emergent model dynamics of NMMs. We combine the classical machine learning approaches of trees and random forests to enable studying the effect that varying multiple parameters has on the dynamics of a model. The method proceeds by using simulations to transform the mathematical model into a database. This database is then used to partition parameter space with respect to dynamic features of interest, using random forests. This allows us to rapidly explore dynamics in high dimensional parameter space, capture the approximate location of qualitative transitions in dynamics and assess the relative importance of all parameters in the model in all dimensions simultaneously. We apply this method to a commonly used NMM in the context of transitions to seizure dynamics. We find that the inhibitory sub-system is most crucial for the generation of seizure dynamics, confirm and expand previous findings regarding the ratio of excitation and inhibition, and demonstrate that previously overlooked parameters can have a significant impact on model dynamics. We advocate the use of this method in future to constrain high dimensional parameter spaces enabling more efficient, person-specific, model calibration. [ABSTRACT FROM AUTHOR]

Reduced gamma-aminobutyric acid (GABA) inhibition has been implicated in both anxiety and epilepsy. GAD65-/- (NOD/LtJ) mice have significantly decreased basal GABA levels in the brain and a lowered threshold for seizure generation. One fifth of GAD65 -/- mice experienced stress-induced seizures upon exposure to an open field at 4 weeks of age. In each successive week until 8 weeks of age, the latency to seizures decreased with prior seizure experience. 100% of GAD65-/- mice exhibited stress-induced seizures by the end of 8 weeks. GAD65-/- mice also exhibited marked impairment in open field exploratory behavior and deficits in spatial learning acquisition on a Barnes maze. Anxiety-like behavior in an open field was observed prior to seizure onset and was predictive of subsequent seizures. Immunohistochemical characterization of interneuron subtypes in GAD65-/- mice showed a selective decrease in GABA and neuropeptide Y (NPY) levels and no change in calbindin (CLB) or calretinin (CLR) immunoreactivity in the hippocampus. Stem cells from the medial ganglionic eminence (MGE) were injected into the hippocampal hilus to restore GABAergic interneurons. One week after transplantation, MGE-transplanted mice demonstrated significant seizure resistance compared to sham surgical controls. The percent area of GFP+ MGE graft in the hippocampus correlated significantly with the increase in seizure latency. Our data indicate that impaired GABAergic neurotransmission can cause anxiety-like behavior and stress-induced seizures that can be rescued by MGE stem cell transplantation. [ABSTRACT FROM AUTHOR]

Epilepsy is one of the most common neurological disorders affecting about 1% of the world population. For patients with focal seizures that cannot be treated with antiepileptic drugs, the common treatment is a surgical procedure for removal of the seizure onset zone (SOZ). In this work we introduce an algorithm for automatic localization of the seizure onset zone (SOZ) in epileptic patients based on electrocorticography (ECoG) recordings. The proposed algorithm builds upon the hypothesis that the abnormal excessive (or synchronous) neuronal activity in the brain leading to seizures starts in the SOZ and then spreads to other areas in the brain. Thus, when this abnormal activity starts, signals recorded at electrodes close to the SOZ should have a relatively large causal influence on the rest of the recorded signals. The SOZ localization is executed in two steps. First, the algorithm represents the set of electrodes using a directed graph in which nodes correspond to recording electrodes and the edges’ weights quantify the pair-wise causal influence between the recorded signals. Then, the algorithm infers the SOZ from the estimated graph using a variant of the PageRank algorithm followed by a novel post-processing phase. Inference results for 19 patients show a close match between the SOZ inferred by the proposed approach and the SOZ estimated by expert neurologists (success rate of 17 out of 19). [ABSTRACT FROM AUTHOR]

Medicinal plants represent a significant reservoir of unexplored substances for early-stage drug discovery. Of interest, two flowering Mediterranean plants have been used for thousands of years for their beneficial effects on nervous disorders, including anxiety and mood. However, the therapeutic potential of these plants regarding their ability to target ion channels and neuronal excitability remains largely unknown. Towards this goal, we have investigated the ability of Lavender and Rosemary to modulate T-type calcium channels (TTCCs). TTCCs play important roles in neuronal excitability, neuroprotection, sensory processes and sleep. These channels are also involved in epilepsy and pain. Using the whole-cell patch-clamp technique, we have characterized how Lavender and Rosemary extracts, as well as their major active compounds Linalool and Rosmarinic acid, modulate the electrophysiological properties of recombinant TTCCs (CaV3.2) expressed in HEK-293T cells. Both the methanolic and essential oil extracts as well as the active compounds of these plants inhibit Cav3.2 current in a concentration-dependent manner. In addition, these products also induce a negative shift of the steady-state inactivation of CaV3.2 current with no change in the activation properties. Taken together, our findings reveal that TTCCs are a molecular target of the Lavender and Rosemary compounds, suggesting that inhibition of TTCCs could contribute to the anxiolytic and the neuroprotective effects of these plants. [ABSTRACT FROM AUTHOR]

Interictal discharges (IIDs) are abnormal waveforms registered in the periods before or between seizures. IIDs that are initiated by GABAergic interneurons have not been mathematically modeled yet. In the present study, a mathematical model that describes the mechanisms of these discharges is proposed. The model is based on the experimental recordings of IIDs in pyramidal neurons of the rat entorhinal cortex and estimations of synaptic conductances during IIDs. IIDs were induced in cortico-hippocampal slices by applying an extracellular solution with 4-aminopyridine, high potassium, and low magnesium concentrations. Two different types of IIDs initiated by interneurons were observed. The first type of IID (IID1) was pure GABAergic. The second type of IID (IID2) was induced by GABAergic excitation and maintained by recurrent interactions of both GABA- and glutamatergic neuronal populations. The model employed the conductance-based refractory density (CBRD) approach, which accurately approximates the firing rate of a population of similar Hodgkin-Huxley-like neurons. The model of coupled excitatory and inhibitory populations includes AMPA, NMDA, and GABA-receptor-mediated synapses and gap junctions. These neurons receive both arbitrary deterministic input and individual colored Gaussian noise. Both types of IIDs were successfully reproduced in the model by setting two different depolarized levels for GABA-mediated current reversal potential. It was revealed that short-term synaptic depression is a crucial factor in ceasing each of the discharges, and it also determines their durations and frequencies. [ABSTRACT FROM AUTHOR]

Background: Preterm birth (<37 gestational weeks) poses a risk of poorer neurocognitive functioning. Faster growth after preterm birth predicts better cognitive abilities and can be promoted through adequate nutrition, but it remains unknown whether variations in nutrient intakes translate into long-term benefits for neurodevelopment. Methods: In 86 participants of the Helsinki Study of Very Low Birth Weight Adults (birthweight <1500g), we examined if higher intakes of energy, macronutrients, and human milk during the first nine weeks after preterm birth predict performance in tests of cognitive ability at 25.1 years of age (SD = 2.1). Results: 10 kcal/kg/day higher total energy intake at 3 to 6 weeks of age was associated with 0.21 SD higher adult IQ (95% Confidence Interval [CI] 0.07–0.35). Higher carbohydrate and fat intake at 3–6 weeks, and higher energy intake from human milk at 3–6 and at 6–9 weeks were also associated with higher adult IQ: these effect sizes ranged from 0.09 SD (95% CI 0.01–0.18) to 0.34 SD (0.14–0.54) higher IQ, per one gram/kg/day more carbohydrate and fat, and per 10 kcal/kg/day more energy from human milk. Adjustment for neonatal complications attenuated the associations: intraventricular hemorrhage, in particular, was associated with both poorer nutrition and poorer IQ. Conclusion: In preterm neonates with very low birth weight, higher energy and human milk intake predict better neurocognitive abilities in adulthood. To understand the determinants of these infants' neurocognitive outcome, it seems important to take into account the role of postnatal nutrition, not just as an isolated exposure, but as a potential mediator between neonatal illness and long-term neurodevelopment. [ABSTRACT FROM AUTHOR]

Chemotherapy aided by opening of the blood-brain barrier with intra-arterial infusion of hyperosmolar mannitol improves the outcome in primary central nervous system lymphoma. Proper opening of the blood-brain barrier is crucial for the treatment, yet there are no means available for its real-time monitoring. The intact blood-brain barrier maintains a mV-level electrical potential difference between blood and brain tissue, giving rise to a measurable electrical signal at the scalp. Therefore, we used direct-current electroencephalography (DC-EEG) to characterize the spatiotemporal behavior of scalp-recorded slow electrical signals during blood-brain barrier opening. Nine anesthetized patients receiving chemotherapy were monitored continuously during 47 blood-brain barrier openings induced by carotid or vertebral artery mannitol infusion. Left or right carotid artery mannitol infusion generated a strongly lateralized DC-EEG response that began with a 2 min negative shift of up to 2000 μV followed by a positive shift lasting up to 20 min above the infused carotid artery territory, whereas contralateral responses were of opposite polarity. Vertebral artery mannitol infusion gave rise to a minimally lateralized and more uniformly distributed slow negative response with a posterior-frontal gradient. Simultaneously performed near-infrared spectroscopy detected a multiphasic response beginning with mannitol-bolus induced dilution of blood and ending in a prolonged increase in the oxy/deoxyhemoglobin ratio. The pronounced DC-EEG shifts are readily accounted for by opening and sealing of the blood-brain barrier. These data show that DC-EEG is a promising real-time monitoring tool for blood-brain barrier disruption augmented drug delivery. [ABSTRACT FROM AUTHOR]

The synchronization among the activities of neural populations in functional regions is one of the most important electrophysiological phenomena in epileptic brains. The spatiotemporal dynamics of phase synchronization was investigated to reveal the reciprocal interaction between different functional regions during epileptogenesis. Local field potentials (LFPs) were recorded simultaneously from the basolateral amygdala (BLA), the cornu ammonis 1 of hippocampus (CA1) and the mediodorsal nucleus of thalamus (MDT) in the mouse amygdala-kindling models during the development of epileptic seizures. The synchronization of LFPs was quantified between BLA, CA1 and MDT using phase-locking value (PLV). During amygdala kindling, behavioral changes (from stage 0 to stage 5) of mice were accompanied by after-discharges (ADs) of similar waveforms appearing almost simultaneously in CA1, MDT, as well as BLA. AD durations were positively related to the intensity of seizures. During seizures at stages 1~2, PLVs remained relatively low and increased dramatically shortly after the termination of the seizures; by contrast, for stages 3~5, PLVs remained a relatively low level during the initial period but increased dramatically before the seizure termination. And in the theta band, the degree of PLV enhancement was positively associated with seizure intensity. The results suggested that during epileptogenesis, the functional regions were kept desynchronized rather than hyper-synchronized during either the initial or the entire period of the seizures; so different dynamic patterns of phase synchronization may be involved in different periods of the epileptogenesis, and this might also reflect that during seizures at different stages, the mechanisms underlying the dynamics of phase synchronization were different. [ABSTRACT FROM AUTHOR]

We studied the effects of non-Markovian power-law voltage dependent conductances on the generation of action potentials and spiking patterns in a Hodgkin-Huxley model. To implement slow-adapting power-law dynamics of the gating variables of the potassium, n, and sodium, m and h, conductances we used fractional derivatives of order η≤1. The fractional derivatives were used to solve the kinetic equations of each gate. We systematically classified the properties of each gate as a function of η. We then tested if the full model could generate action potentials with the different power-law behaving gates. Finally, we studied the patterns of action potential that emerged in each case. Our results show the model produces a wide range of action potential shapes and spiking patterns in response to constant current stimulation as a function of η. In comparison with the classical model, the action potential shapes for power-law behaving potassium conductance (n gate) showed a longer peak and shallow hyperpolarization; for power-law activation of the sodium conductance (m gate), the action potentials had a sharp rise time; and for power-law inactivation of the sodium conductance (h gate) the spikes had wider peak that for low values of η replicated pituitary- and cardiac-type action potentials. With all physiological parameters fixed a wide range of spiking patterns emerged as a function of the value of the constant input current and η, such as square wave bursting, mixed mode oscillations, and pseudo-plateau potentials. Our analyses show that the intrinsic memory trace of the fractional derivative provides a negative feedback mechanism between the voltage trace and the activity of the power-law behaving gate variable. As a consequence, power-law behaving conductances result in an increase in the number of spiking patterns a neuron can generate and, we propose, expand the computational capacity of the neuron. [ABSTRACT FROM AUTHOR]

Disinhibition of the cortex (e.g., by GABA -receptor blockade) generates synchronous and oscillatory electrophysiological activity that propagates along the cortex. We have studied, in brain slices of the cingulate cortex of mice (postnatal age 14–20 days), the propagation along layer 2/3 as well as the interhemispheric propagation through the corpus callosum of synchronous discharges recorded extracellularly and evoked in the presence of 10 μM bicuculline by electrical stimulation of layer 1. The latency of the responses obtained at the same distance from the stimulus electrode was longer in anterior cingulate cortex (ACC: 39.53 ± 2.83 ms, n = 7) than in retrosplenial cortex slices (RSC 21.99 ± 2.75 ms, n = 5; p<0.05), which is equivalent to a lower propagation velocity in the dorso-ventral direction in ACC than in RSC slices (43.0 mm/s vs 72.9 mm/s). We studied the modulation of this propagation by serotonin. Serotonin significantly increased the latency of the intracortical synchronous discharges (18.9% in the ipsilateral hemisphere and 40.2% in the contralateral hemisphere), and also increased the interhemispheric propagation time by 86.4%. These actions of serotonin were mimicked by the activation of either 5-HT1B or 5-HT2A receptors, but not by the activation of the 5-HT1A subtype. These findings provide further knowledge about the propagation of synchronic electrical activity in the cerebral cortex, including its modulation by serotonin, and suggest the presence of deep differences between the ACC and RSC in the structure of the local cortical microcircuits underlying the propagation of synchronous discharges. [ABSTRACT FROM AUTHOR]

Although there are now a number of antiepileptic drugs (AEDs) available, approximately one-third of epilepsy patients respond poorly to drug intervention. The reasons for this are complex, but are probably reflective of the increasing number of identified mutations that predispose individuals to this disease. Thus, there is a clear requirement for the development of novel treatments to address this unmet clinical need. The existence of gene mutations that mimic a seizure-like behaviour in the fruit fly, Drosophila melanogaster, offers the possibility to exploit the powerful genetics of this insect to identify novel cellular targets to facilitate design of more effective AEDs. In this study we use neuronal expression of GCaMP, a potent calcium reporter, to image neuronal activity using a non-invasive and rapid method. Expression in motoneurons in the isolated CNS of third instar larvae shows waves of calcium-activity that pass between segments of the ventral nerve cord. Time between calcium peaks, in the same neurons, between adjacent segments usually show a temporal separation of greater than 200 ms. Exposure to proconvulsants (picrotoxin or 4-aminopyridine) reduces separation to below 200 ms showing increased synchrony of activity across adjacent segments. Increased synchrony, characteristic of epilepsy, is similarly observed in genetic seizure mutants: bangsenseless1 (bss1) and paralyticK1270T (paraK1270T). Exposure of bss1 to clinically-used antiepileptic drugs (phenytoin or gabapentin) significantly reduces synchrony. In this study we use the measure of synchronicity to evaluate the effectiveness of known and novel anticonvulsive compounds (antipain, isethionate, etopiside rapamycin and dipyramidole) to reduce seizure-like CNS activity. We further show that such compounds also reduce the Drosophila voltage-gated persistent Na+ current (INaP) in an identified motoneuron (aCC). Our combined assays provide a rapid and reliable method to screen unknown compounds for potential to function as anticonvulsants. [ABSTRACT FROM AUTHOR]

In retinitis pigmentosa – a degenerative disease which often leads to incurable blindness- the loss of photoreceptors deprives the retina from a continuous excitatory input, the so-called dark current. In rodent models of this disease this deprivation leads to oscillatory electrical activity in the remaining circuitry, which is reflected in the rhythmic spiking of retinal ganglion cells (RGCs). It remained unclear, however, if the rhythmic RGC activity is attributed to circuit alterations occurring during photoreceptor degeneration or if rhythmic activity is an intrinsic property of healthy retinal circuitry which is masked by the photoreceptor’s dark current. Here we tested these hypotheses by inducing and analysing oscillatory activity in adult healthy (C57/Bl6) and blind mouse retinas (rd10 and rd1). Rhythmic RGC activity in healthy retinas was detected upon partial photoreceptor bleaching using an extracellular high-density multi-transistor-array. The mean fundamental spiking frequency in bleached retinas was 4.3 Hz; close to the RGC rhythm detected in blind rd10 mouse retinas (6.5 Hz). Crosscorrelation analysis of neighbouring wild-type and rd10 RGCs (separation distance <200 µm) reveals synchrony among homologous RGC types and a constant phase shift (∼70 msec) among heterologous cell types (ON versus OFF). The rhythmic RGC spiking in these retinas is driven by a network of presynaptic neurons. The inhibition of glutamatergic ganglion cell input or the inhibition of gap junctional coupling abolished the rhythmic pattern. In rd10 and rd1 retinas the presynaptic network leads to local field potentials, whereas in bleached retinas additional pharmacological disinhibition is required to achieve detectable field potentials. Our results demonstrate that photoreceptor bleaching unmasks oscillatory activity in healthy retinas which shares many features with the functional phenotype detected in rd10 retinas. The quantitative physiological differences advance the understanding of the degeneration process and may guide future rescue strategies. [ABSTRACT FROM AUTHOR]

S100B is a reporter of blood-brain barrier (BBB) integrity which appears in blood when the BBB is breached. Circulating S100B derives from either extracranial sources or release into circulation by normal fluctuations in BBB integrity or pathologic BBB disruption (BBBD). Elevated S100B matches the clinical presence of indices of BBBD (gadolinium enhancement or albumin coefficient). After repeated sub-concussive episodes, serum S100B triggers an antigen-driven production of anti-S100B autoantibodies. We tested the hypothesis that the presence of S100B in extracranial tissue is due to peripheral cellular uptake of serum S100B by antigen presenting cells, which may induce the production of auto antibodies against S100B. To test this hypothesis, we used animal models of seizures, enrolled patients undergoing repeated BBBD, and collected serum samples from epileptic patients. We employed a broad array of techniques, including immunohistochemistry, RNA analysis, tracer injection and serum analysis. mRNA for S100B was segregated to barrier organs (testis, kidney and brain) but S100B protein was detected in immunocompetent cells in spleen, thymus and lymph nodes, in resident immune cells (Langerhans, satellite cells in heart muscle, etc.) and BBB endothelium. Uptake of labeled S100B by rat spleen CD4+ or CD8+ and CD86+ dendritic cells was exacerbated by pilocarpine-induced status epilepticus which is accompanied by BBBD. Clinical seizures were preceded by a surge of serum S100B. In patients undergoing repeated therapeutic BBBD, an autoimmune response against S100B was measured. In addition to its role in the central nervous system and its diagnostic value as a BBBD reporter, S100B may integrate blood-brain barrier disruption to the control of systemic immunity by a mechanism involving the activation of immune cells. We propose a scenario where extravasated S100B may trigger a pathologic autoimmune reaction linking systemic and CNS immune responses. [ABSTRACT FROM AUTHOR]

Pleiotrophin (PTN) is an extracellular matrix-associated protein with neurotrophic and neuroprotective effects that is involved in a variety of neurodevelopmental processes. Data regarding the cognitive-behavioral and neuroanatomical phenotype of pleiotrophin knockout (KO) mice is limited. The purpose of this study was to more fully characterize this phenotype, with emphasis on the domains of learning and memory, cognitive-behavioral flexibility, exploratory behavior and anxiety, social behavior, and the neuronal and vascular microstructure of the lateral entorhinal cortex (EC). PTN KOs exhibited cognitive rigidity, heightened anxiety, behavioral reticence in novel contexts and novel social interactions suggestive of neophobia, and lamina-specific decreases in neuronal area and increases in neuronal density in the lateral EC. Initial learning of spatial and other associative tasks, as well as vascular density in the lateral EC, was normal in the KOs. These data suggest that the absence of PTN in vivo is associated with disruption of specific cognitive and affective processes, raising the possibility that further study of PTN KOs might have implications for the study of human disorders with similar features. [ABSTRACT FROM AUTHOR]

Epilepsy and other seizure disorders are not adequately managed with currently available drugs. We recently synthesized a series of dibromophenyl enaminones and demonstrated that AK6 and E249 were equipotent to previous analogs but more efficacious in suppressing neuronal excitation. Here we examined the actions of these lead compounds on in vitro and in vivo seizure models. In vitro seizures were induced in the hippocampal slice chemically (zero Mg2+ buffer and picrotoxin) and electrically using patterned high frequency stimulation (HFS) of afferents. In vivo seizures were induced in rats using the 6 Hz and the maximal electroshock models. AK6 (10 µM) and E249 (10 µM) depressed the amplitude of population spikes recorded in area CA1 of the hippocampus by −50.5±4.3% and −40.1±3.1% respectively, with partial recovery after washout. In the zero Mg2+ model, AK6 (10 µM) depressed multiple population spiking (mPS) by −59.3±6.9% and spontaneous bursts (SBs) by −65.9±7.2% and in the picrotoxin-model by −43.3±7.2% and −50.0±8.3%, respectively. Likewise, E249 (10 µM) depressed the zero-Mg2+-induced mPS by −48.8±9.5% and SBs by −55.8±15.5%, and in the picrotoxin model by −37.1±5.5% and −56.5±11.4%, respectively. They both suppressed post-HFS induced afterdischarges and SBs. AK6 and E249 dose-dependently protected rats in maximal electroshock and 6 Hz models of in vivo seizures after 30 min pretreatment. Their level of protection in both models was similar to that obtained with phenytoin Finally, while AK6 had no effect on locomotion in rats, phenytoin significantly decreased locomotion. AK6 and E249, suppressed in vitro and in vivo seizures to a similar extent. Their in vivo activities are comparable with but not superior to phenytoin. The most efficacious, AK6 produced no locomotor suppression while phenytoin did. Thus, AK6 and E249 may be excellent candidates for further investigation as potential agents for the treatment of epilepsy syndromes with possibly less CNS side effects. [ABSTRACT FROM AUTHOR]

Accurate spatial localization requires a mechanism that corrects for errors, which might arise from inaccurate sensory information or neuronal noise. In this paper, we propose that Hippocampal place cells might implement such an error correction mechanism by integrating different sources of information in an approximately Bayes-optimal fashion. We compare the predictions of our model with physiological data from rats. Our results suggest that useful predictions regarding the firing fields of place cells can be made based on a single underlying principle, Bayesian cue integration, and that such predictions are possible using a remarkably small number of model parameters. [ABSTRACT FROM AUTHOR]

Epilepsy is a disorder characterized by excessive synchronized neural activity. The hippocampus and surrounding temporal lobe structures appear particularly sensitive to epileptiform activity. Somatostatin (SST)-positive interneurons within the hilar region have been suggested to gate hippocampal activity, and therefore may play a crucial role in the dysregulation of hippocampal activity. In this study, we examined SST interneuron activity in the in vitro 4-aminopyridine (4-AP) model of epilepsy. We employed a multi-disciplinary approach, combining extracellular multi-electrode array (MEA) recordings with patch-clamp recordings and optical imaging using a genetically encoded calcium sensor. We observed that hilar SST interneurons are strongly synchronized during 4-AP-induced local field potentials (LFPs), as assayed by Ca2+ imaging as well as juxtacellular or intracellular recording. SST interneurons were particularly responsive to GABA-mediated LFPs that occurred in the absence of ionotropic glutamatergic transmission. Our results present evidence that the extensive synchronized activity of SST-expressing interneurons contribute to the generation of GABAergic LFPs in an in vitro model of temporal lobe seizures. [ABSTRACT FROM AUTHOR]

Epileptic seizure is a paroxysmal and self-limited phenomenon characterized by abnormal hypersynchrony of a large population of neurons. However, our current understanding of seizure dynamics is still limited. Here we propose a novel in vivo model of seizure-like afterdischarges using optogenetics, and report on investigation of directional network dynamics during seizure along the septo-temporal (ST) axis of hippocampus. Repetitive pulse photostimulation was applied to the rodent hippocampus, in which channelrhodopsin-2 (ChR2) was expressed, under simultaneous recording of local field potentials (LFPs). Seizure-like afterdischarges were successfully induced after the stimulation in both W-TChR2V4 transgenic (ChR2V-TG) rats and in wild type rats transfected with adeno-associated virus (AAV) vectors carrying ChR2. Pulse frequency at 10 and 20 Hz, and a 0.05 duty ratio were optimal for afterdischarge induction. Immunohistochemical c-Fos staining after a single induced afterdischarge confirmed neuronal activation of the entire hippocampus. LFPs were recorded during seizure-like afterdischarges with a multi-contact array electrode inserted along the ST axis of hippocampus. Granger causality analysis of the LFPs showed a bidirectional but asymmetric increase in signal flow along the ST direction. State space presentation of the causality and coherence revealed three discrete states of the seizure-like afterdischarge phenomenon: 1) resting state; 2) afterdischarge initiation with moderate coherence and dominant septal-to-temporal causality; and 3) afterdischarge termination with increased coherence and dominant temporal-to-septal causality. A novel in vivo model of seizure-like afterdischarge was developed using optogenetics, which was advantageous in its reproducibility and artifact-free electrophysiological observations. Our results provide additional evidence for the potential role of hippocampal septo-temporal interactions in seizure dynamics in vivo. Bidirectional networks work hierarchically along the ST hippocampus in the genesis and termination of epileptic seizures. [ABSTRACT FROM AUTHOR]