Multineuron firing patterns are often observed, yet are predicted to be rare by models that assume independent firing. To explain these correlated network states, two groups recently applied a second-order maximum entropy model that used only observed firing rates and pairwise interactions as parameters (Schneidman et al., 2006; Shlens et al., 2006). Interestingly, with these minimal assumptions they predicted 90 -99% of network correlations. If generally applicable, this approach could vastly simplify analyses of complex networks. However, this initial work was done largely on retinal tissue, and its applicability to cortical circuits is mostly unknown. This work also did not address the temporal evolution of correlated states. To investigate these issues, we applied the model to multielectrode data containing spontaneous spikes or local field potentials from cortical slices and cultures. The model worked slightly less well in cortex than in retina, accounting for 88 Ϯ 7% (mean Ϯ SD) of network correlations. In addition, in 8 of 13 preparations, the observed sequences of correlated states were significantly longer than predicted by concatenating states from the model. This suggested that temporal dependencies are a common feature of cortical network activity, and should be considered in future models. We found a significant relationship between strong pairwise temporal correlations and observed sequence length, suggesting that pairwise temporal correlations may allow the model to be extended into the temporal domain. We conclude that although a second-order maximum entropy model successfully predicts correlated states in cortical networks, it should be extended to account for temporal correlations observed between states.
Perampanel [Fycompa, 2-(2-oxo-1-phenyl-5-pyridin-2-yl-1,2-dihydropyridin-3-yl)benzonitrile hydrate 4:3; Eisai Inc., Woodcliff Lake, NJ] is an AMPA (a-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) receptor antagonist used as an adjunctive treatment of partial-onset seizures. We asked whether perampanel has AMPA receptor antagonist activity in both the cerebral cortex and hippocampus associated with antiepileptic efficacy and also in the cerebellum associated with motor side effects in rodent and human brains. We also asked whether epileptic or nonepileptic human cortex is similarly responsive to AMPA receptor antagonism by perampanel. In rodent models, perampanel decreased epileptic-like activity in multiple seizure models. However, doses of perampanel that had anticonvulsant effects were within the same range as those engendering motor side effects. Perampanel inhibited native rat and human AMPA receptors from the hippocampus as well as the cerebellum that were reconstituted into Xenopus oocytes. In addition, with the same technique, we found that perampanel inhibited AMPA receptors from hippocampal tissue that had been removed from a patient who underwent surgical resection for refractory epilepsy. Perampanel inhibited AMPA receptor-mediated ion currents from all the tissues investigated with similar potency (IC 50 values ranging from 2.6 to 7.0 mM). Cortical slices from the left temporal lobe derived from the same patient were studied in a 60-microelectrode array. Large field potentials were evoked on at least 45 channels of the array, and 10 mM perampanel decreased their amplitude and firing rate. Perampanel also produced a 33% reduction in the branching parameter, demonstrating the effects of perampanel at the network level. These data suggest that perampanel blocks AMPA receptors globally across the brain to account for both its antiepileptic and sideeffect profile in rodents and epileptic patients.
Understanding how ensembles of neurons collectively interact will be a key step in developing a mechanistic theory of cognitive processes. Recent progress in multineuron recording and analysis techniques has generated tremendous excitement over the physiology of living neural networks. One of the key developments driving this interest is a new class of models based on the principle of maximum entropy. Maximum entropy models have been reported to account for spatial correlation structure in ensembles of neurons recorded from several different types of data. Importantly, these models require only information about the firing rates of individual neurons and their pairwise correlations. If this approach is generally applicable, it would drastically simplify the problem of understanding how neural networks behave. Given the interest in this method, several groups now have worked to extend maximum entropy models to account for temporal correlations. Here, we review how maximum entropy models have been applied to neuronal ensemble data to account for spatial and temporal correlations. We also discuss criticisms of the maximum entropy approach that argue that it is not generally applicable to larger ensembles of neurons. We conclude that future maximum entropy models will need OPEN ACCESSEntropy 2010, 12 90 to address three issues: temporal correlations, higher-order correlations, and larger ensemble sizes. Finally, we provide a brief list of topics for future research.
HZ-166 has previously been characterized as an α2,3-selective GABA receptor modulator with anticonvulsant, anxiolytic, and anti-nociceptive properties but reduced motor effects. We discovered a series of ester bioisosteres with reduced metabolic liabilities, leading to improved efficacy as anxiolytic-like compounds in rats. In the present study, we evaluated the anticonvulsant effects KRM-II-81 across several rodent models. In some models we also evaluated key structural analogs. KRM-II-81 suppressed hyper-excitation in a network of cultured cortical neurons without affecting the basal neuronal activity. KRM-II-81 was active against electroshock-induced convulsions in mice, pentylenetetrazole (PTZ)-induced convulsions in rats, elevations in PTZ-seizure thresholds, and amygdala-kindled seizures in rats with efficacies greater than that of diazepam. KRM-II-81 was also active in the 6 Hz seizure model in mice. Structural analogs of KRM-II-81 but not the ester, HZ-166, were active in all models in which they were evaluated. We further evaluated KRM-II-81 in human cortical epileptic tissue where it was found to significantly-attenuate picrotoxin- and AP-4-induced increases in firing rate across an electrode array. These molecules generally had a wider margin of separation in potencies to produce anticonvulsant effects vs. motor impairment on an inverted screen test than did diazepam. Ester bioisosters of HZ-166 are thus presented as novel agents for the potential treatment of epilepsy acting via selective positive allosteric amplification of GABA signaling through α2/α3-containing GABA receptors. The in vivo data from the present study can serve as a guide to dosing parameters that predict engagement of central GABA receptors.
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