Strength and duration of perisomatic GABAergic inhibition depend on distance between synaptically connected cells.

GABAergic perisoma-inhibiting fast-spiking interneurons (PIIs) effectively control the activity of large neuron populations by their wide axonal arborizations. It is generally assumed that the output of one PII to its target cells is strong and rapid. Here, we show that, unexpectedly, both strength and time course of PII-mediated perisomatic inhibition change with distance between synaptically connected partners in the rodent hippocampus. Synaptic signals become weaker due to lower contact numbers and decay more slowly with distance, very likely resulting from changes in GABAA receptor subunit composition. When distance-dependent synaptic inhibition is introduced to a rhythmically active neuronal network model, randomly driven principal cell assemblies are strongly synchronized by the PIIs, leading to higher precision in principal cell spike times than in a network with uniform synaptic inhibition.

Morpho-physiological criteria divide dentate gyrus interneurons into classes.

GABAergic inhibitory interneurons control fundamental aspects of neuronal network function. Their functional roles are assumed to be defined by the identity of their input synapses, the architecture of their dendritic tree, the passive and active membrane properties and finally the nature of their postsynaptic targets. Indeed, interneurons display a high degree of morphological and physiological heterogeneity. However, whether their morphological and physiological characteristics are correlated and whether interneuron diversity can be described by a continuum of GABAergic cell types or by distinct classes has remained unclear. Here we perform a detailed morphological and physiological characterization of GABAergic cells in the dentate gyrus, the input region of the hippocampus. To achieve an unbiased and efficient sampling and classification we used knock-in mice expressing the enhanced green fluorescent protein (eGFP) in glutamate decarboxylase 67 (GAD67)-positive neurons and performed cluster analysis. We identified five interneuron classes, each of them characterized by a distinct set of anatomical and physiological parameters. Cross-correlation analysis further revealed a direct relation between morphological and physiological properties indicating that dentate gyrus interneurons fall into functionally distinct classes which may differentially control neuronal network activity.

Spine plasticity of dentate gyrus parvalbumin-positive interneurons is regulated by experience.

Experience-driven alterations in neuronal activity are followed by structural-functional modifications allowing cells to adapt to these activity changes. Structural plasticity has been observed for cortical principal cells. However, how GABAergic interneurons respond to experience-dependent network activity changes is not well understood. We show that parvalbumin-expressing interneurons (PVIs) of the dentate gyrus (DG) possess dendritic spines, which undergo behaviorally induced structural dynamics. Glutamatergic inputs at PVI spines evoke signals with high spatial compartmentalization defined by neck length. Mice experiencing novel contexts form more PVI spines with elongated necks and exhibit enhanced network and PVI activity and cFOS expression. Enhanced green fluorescent protein reconstitution across synaptic partner-mediated synapse labeling shows that experience-driven PVI spine growth boosts targeting of PVI spines over shafts by glutamatergic synapses. Our findings propose a role for PVI spine dynamics in regulating PVI excitation by their inputs, which may allow PVIs to dynamically adjust their functional integration in the DG microcircuitry in relation to network computational demands.

Interneurons provide circuit-specific depolarization and hyperpolarization.

Perisoma-inhibiting interneurons (PIIs) control fundamental aspects of cortical network function by means of their GABAergic output synapses. However, whether they depolarize or hyperpolarize their target cells in the mature circuitry remains controversial. By using unitary field potential and gramicidin D perforated-patch recordings, we provide evidence that the postsynaptic effect of GABAergic synapses is fundamentally different in two regions of rat hippocampus. Signaling at PII output synapses is hyperpolarizing in CA1 principal cells (PCs) but depolarizing in dentate gyrus (DG) PCs. While the reversal potential of GABA(A) receptor-mediated currents is identical in both areas, ∼15 mV more negative resting potentials of DG compared with CA1 PCs underlie the opposing effects of perisomatic GABAergic transmission. Thus, the nature of PII output signaling is circuit-dependent and may therefore contribute differentially to information processing in the two brain areas.

Inhibitory networks of fast-spiking interneurons generate slow population activities due to excitatory fluctuations and network multistability.

Slow population activities (SPAs) exist in the brain and have frequencies below ~5 Hz. Despite SPAs being prominent in several cortical areas and serving many putative functions, their mechanisms are not well understood. We studied a specific type of in vitro GABAergic, inhibition-based SPA exhibited by C57BL/6 murine hippocampus. We used a multipronged approach consisting of experiment, simulation, and mathematical analyses to uncover mechanisms responsible for hippocampal SPAs. Our results show that hippocampal SPAs are an emergent phenomenon in which the "slowness" of the network is due to interactions between synaptic and cellular characteristics of individual fast-spiking, inhibitory interneurons. Our simulations quantify characteristics underlying hippocampal SPAs. In particular, for hippocampal SPAs to occur, we predict that individual fast-spiking interneurons should have frequency-current (f-I) curves that exhibit a suitably sized kink where the slope of the curve decreases more abruptly in the gamma frequency range with increasing current. We also predict that these interneurons should be well connected with one another. Our mathematical analyses show that the combination of synaptic and intrinsic conditions, as predicted by our simulations, promotes network multistability. Population slow timescales occur when excitatory fluctuations drive the network between different stable network firing states. Since many of the parameters we use are extracted from experiments and subsequent measurements of experimental f-I curves of fast-spiking interneurons exhibit characteristics as predicted, we propose that our network models capture a fundamental operating mechanism in biological hippocampal networks.

Determinants of quality of life in adults with epilepsy: a multicenter, cross-sectional study from Germany.

BACKGROUND: Assessment of quality of life (QoL) has become an important indicator for chronic neurological diseases. While these conditions often limit personal independence and autonomy, they are also associated with treatment-related problems and reduced life expectancy. Epilepsy has a tremendous impact on the QoL of patients and their families, which is often underestimated by practitioners. The aim of this work was to identify relevant factors affecting QoL in adults with epilepsy. METHODS: This cross-sectional, multicenter study was conducted at four specialized epilepsy centers in Germany. Patients diagnosed with epilepsy completed a standardized questionnaire focusing on QoL and aspects of healthcare in epilepsy. Univariate regression analyses and pairwise comparisons were performed to identify variables of decreased QoL represented by the overall Quality of Life in Epilepsy Inventory (QOLIE-31) score. The variables were then considered in a multivariate regression analysis after multicollinearity analysis. RESULTS: Complete datasets for the QOLIE-31 were available for 476 patients (279 [58.6%] female, 197 [41.4%] male, mean age 40.3 years [range 18-83 years]). Multivariate regression analysis revealed significant associations between low QoL and a high score on the Liverpool Adverse Events Profile (LAEP; beta=-0.28, p < 0.001), Hospital Anxiety and Depression Scale - depression subscale (HADS-D; beta=-0.27, p < 0.001), Neurological Disorders Depression Inventory in Epilepsy (NDDI-E; beta=-0.19, p < 0.001), revised Epilepsy Stigma Scale (beta=-0.09, p = 0.027), or Seizure Worry Scale (beta=-0.18, p < 0.001) and high seizure frequency (beta = 0.14, p < 0.001). CONCLUSION: Epilepsy patients had reduced QoL, with a variety of associated factors. In addition to disease severity, as measured by seizure frequency, the patient's tolerability of anti-seizure medications and the presence of depression, stigma, and worry about new seizures were strongly associated with poor QoL. Diagnosed comorbid depression was underrepresented in the cohort; therefore, therapeutic decisions should always consider individual psychobehavioral and disease-specific aspects. Signs of drug-related adverse events, depression, fear, or stigmatization should be actively sought to ensure that patients receive personalized and optimized treatment. TRIAL REGISTRATION: German Clinical Trials Register (DRKS00022024; Universal Trial Number: U1111-1252-5331).

Parvalbumin expressing interneurons control spike-phase coupling of hippocampal cells to theta oscillations.

Encoding of information by hippocampal neurons is defined by the number and the timing of action potentials generated relative to ongoing network oscillations in the theta (5-14 Hz), gamma (30-80 Hz) and ripple frequency range (150-200 Hz). The exact mechanisms underlying the temporal coupling of action potentials of hippocampal cells to the phase of rhythmic network activity are not fully understood. One critical determinant of action potential timing is synaptic inhibition provided by a complex network of Gamma-amino-hydroxy-butyric acid releasing (GABAergic) interneurons. Among the various GABAergic cell types, particularly Parvalbumin-expressing cells are powerful regulators of neuronal activity. Here we silenced Parvalbumin-expressing interneurons in hippocampal areas CA1 and the dentate gyrus in freely moving mice using the optogenetic silencing tool eNpHR to determine their influence on spike timing in principal cells. During optogenetic inhibition of Parvalbumin-expressing cells, local field potential recordings revealed no change in power or frequency of CA1 or dentate gyrus network oscillations. However, CA1 pyramidal neurons exhibited significantly reduced spike-phase coupling to CA1 theta, but not gamma or ripple oscillations. These data suggest that hippocampal Parvalbumin-expressing interneurons are particularly important for an intact theta-based temporal coding scheme of hippocampal principal cell populations.

Repetitive Electroencephalography as Biomarker for the Prediction of Survival in Patients with Post-Hypoxic Encephalopathy.

Predicting survival in patients with post-hypoxic encephalopathy (HE) after cardiopulmonary resuscitation is a challenging aspect of modern neurocritical care. Here, continuous electroencephalography (cEEG) has been established as the gold standard for neurophysiological outcome prediction. Unfortunately, cEEG is not comprehensively available, especially in rural regions and developing countries. The objective of this monocentric study was to investigate the predictive properties of repetitive EEGs (rEEGs) with respect to 12-month survival based on data for 199 adult patients with HE, using log-rank and multivariate Cox regression analysis (MCRA). A total number of 59 patients (29.6%) received more than one EEG during the first 14 days of acute neurocritical care. These patients were analyzed for the presence of and changes in specific EEG patterns that have been shown to be associated with favorable or poor outcomes in HE. Based on MCRA, an initially normal amplitude with secondary low-voltage EEG remained as the only significant predictor for an unfavorable outcome, whereas all other relevant parameters identified by univariate analysis remained non-significant in the model. In conclusion, rEEG during early neurocritical care may help to assess the prognosis of HE patients if cEEG is not available.

Recording Spatially Restricted Oscillations in the Hippocampus of Behaving Mice.

The local field potential (LFP) emerges from ion movements across neural membranes. Since the voltage recorded by LFP electrodes reflects the summed electrical field of a large volume of brain tissue, extracting information about local activity is challenging. Studying neuronal microcircuits, however, requires a reliable distinction between truly local events and volume-conducted signals originating in distant brain areas. Current source density (CSD) analysis offers a solution for this problem by providing information about current sinks and sources in the vicinity of the electrodes. In brain areas with laminar cytoarchitecture such as the hippocampus, one-dimensional CSD can be obtained by estimating the second spatial derivative of the LFP. Here, we describe a method to record multilaminar LFPs using linear silicon probes implanted into the dorsal hippocampus. CSD traces are computed along individual shanks of the probe. This protocol thus describes a procedure to resolve spatially restricted neuronal network oscillations in the hippocampus of freely moving mice.

Distance-dependent inhibition facilitates focality of gamma oscillations in the dentate gyrus.

Gamma oscillations (30-150 Hz) in neuronal networks are associated with the processing and recall of information. We measured local field potentials in the dentate gyrus of freely moving mice and found that gamma activity occurs in bursts, which are highly heterogeneous in their spatial extensions, ranging from focal to global coherent events. Synaptic communication among perisomatic-inhibitory interneurons (PIIs) is thought to play an important role in the generation of hippocampal gamma patterns. However, how neuronal circuits can generate synchronous oscillations at different spatial scales is unknown. We analyzed paired recordings in dentate gyrus slices and show that synaptic signaling at interneuron-interneuron synapses is distance dependent. Synaptic strength declines whereas the duration of inhibitory signals increases with axonal distance among interconnected PIIs. Using neuronal network modeling, we show that distance-dependent inhibition generates multiple highly synchronous focal gamma bursts allowing the network to process complex inputs in parallel in flexibly organized neuronal centers.Perisomatic-inhibitory interneurons (PIIs) contribute to the generation of gamma oscillations in the hippocampus. Here the authors demonstrate distance-dependent inhibition between PIIs in freely moving mice, and use computational analysis to show that distance-dependent inhibition supports the emergence of focal gamma bursts.

Impaired fast-spiking interneuron function in a genetic mouse model of depression.

Rhythmic neuronal activity provides a frame for information coding by co-active cell assemblies. Abnormal brain rhythms are considered as potential pathophysiological mechanisms causing mental disease, but the underlying network defects are largely unknown. We find that mice expressing truncated Disrupted-in-Schizophrenia 1 (Disc1), which mirror a high-prevalence genotype for human psychiatric illness, show depression-related behavior. Theta and low-gamma synchrony in the prelimbic cortex (PrlC) is impaired in Disc1 mice and inversely correlated with the extent of behavioural despair. While weak theta activity is driven by the hippocampus, disturbance of low-gamma oscillations is caused by local defects of parvalbumin (PV)-expressing fast-spiking interneurons (FS-INs). The number of FS-INs is reduced, they receive fewer excitatory inputs, and form fewer release sites on targets. Computational analysis indicates that weak excitatory input and inhibitory output of FS-INs may lead to impaired gamma oscillations. Our data link network defects with a gene mutation underlying depression in humans.