Neuronal Information Processing Research Articles

Recent Trends in the Discovery of Small Molecule Blockers of Sodium Channels.

Voltage-gated sodium channels (VGSC) are responsible for the selective influx of sodium ions in excitable cells. A number of physiological phenomena such as muscle contraction, pain sensation, processing of neuronal information in the brain as well as neuronal regulation of peripheral tissues rely on the activity of these channels. On the other hand, abnormal activity of VGSC are implicated in several pathological processes (e.g., cardiac arrhythmias, epilepsy, and chronic pain) which in some cases (e.g., channelopathies such as myotonias) are linked to specific gene mutations. As a result, VGSC have never stopped attracting the attention of medicinal chemists and the quest for novel drugs to treat these ion channels-associated diseases continues. In this review, VGSC blocking agents reported in the last lustrum are scrutinised with the aim to give a medicinal chemistry perspective on the most interesting compounds classified on the basis of (i) potential therapeutic application, (ii) targeted VGSC isoforms, and (iii) chemical scaffolds. Finally, the clinical potential of selected drug candidates from each chemotype is evaluated by comparing their ligand efficiency metrics. Possible routes for improvement of these preclinical candidates are also discussed.

Near-Infrared Spectroscopy - Electroencephalography-Based Brain-State-Dependent Electrotherapy: A Computational Approach Based on Excitation-Inhibition Balance Hypothesis.

Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The poststroke chronic disability may be ameliorated with early neuro rehabilitation where non-invasive brain stimulation (NIBS) techniques can be used as an adjuvant treatment to hasten the effects. However, the heterogeneity in the lesioned brain will require individualized NIBS intervention where innovative neuroimaging technologies of portable electroencephalography (EEG) and functional-near-infrared spectroscopy (fNIRS) can be leveraged for Brain State Dependent Electrotherapy (BSDE). In this hypothesis and theory article, we propose a computational approach based on excitation–inhibition (E–I) balance hypothesis to objectively quantify the poststroke individual brain state using online fNIRS–EEG joint imaging. One of the key events that occurs following Stroke is the imbalance in local E–I (that is the ratio of Glutamate/GABA), which may be targeted with NIBS using a computational pipeline that includes individual “forward models” to predict current flow patterns through the lesioned brain or brain target region. The current flow will polarize the neurons, which can be captured with E–I-based brain models. Furthermore, E–I balance hypothesis can be used to find the consequences of cellular polarization on neuronal information processing, which can then be implicated in changes in function. We first review the evidence that shows how this local imbalance between E–I leading to functional dysfunction can be restored in targeted sites with NIBS (motor cortex and somatosensory cortex) resulting in large-scale plastic reorganization over the cortex, and probably facilitating recovery of functions. Second, we show evidence how BSDE based on E–I balance hypothesis may target a specific brain site or network as an adjuvant treatment. Hence, computational neural mass model-based integration of neurostimulation with online neuroimaging systems may provide less ambiguous, robust optimization of NIBS, and its application in neurological conditions and disorders across individual patients.

A Local Learning Rule for Independent Component Analysis.

Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering.

Sox11 Balances Dendritic Morphogenesis with Neuronal Migration in the Developing Cerebral Cortex.

The coordinated mechanisms balancing promotion and suppression of dendritic morphogenesis are crucial for the development of the cerebral cortex. Although previous studies have revealed important transcription factors that promote dendritic morphogenesis during development, those that suppress dendritic morphogenesis are still largely unknown. Here we found that the expression levels of the transcription factor Sox11 decreased dramatically during dendritic morphogenesis. Our loss- and gain-of-function studies using postnatal electroporation and in utero electroporation indicate that Sox11 is necessary and sufficient for inhibiting dendritic morphogenesis of excitatory neurons in the mouse cerebral cortex during development. Interestingly, we found that precocious suppression of Sox11 expression caused precocious branching of neurites and a neuronal migration defect. We also found that the end of radial migration induced the reduction of Sox11 expression. These findings indicate that suppression of dendritic morphogenesis by Sox11 during radial migration is crucial for the formation of the cerebral cortex. Because dendritic morphology has profound impacts on neuronal information processing, the mechanisms underlying dendritic morphogenesis during development are of great interest. Our loss- and gain-of-function studies indicate that Sox11 is necessary and sufficient for inhibiting dendritic morphogenesis of excitatory neurons in the mouse cerebral cortex during development. Interestingly, we found that precocious suppression of Sox11 expression caused a neuronal migration defect. These findings indicate that suppression of dendritic morphogenesis by Sox11 during radial migration is crucial for the formation of the cerebral cortex.

Hypocellularity in the Murine Model for Down Syndrome Ts65Dn Is Not Affected by Adult Neurogenesis.

Down syndrome (DS) is caused by the presence of an extra copy of the chromosome 21 and it is the most common aneuploidy producing intellectual disability. Neural mechanisms underlying this alteration may include defects in the formation of neuronal networks, information processing and brain plasticity. The murine model for DS, Ts65Dn, presents reduced adult neurogenesis. This reduction has been suggested to underlie the hypocellularity of the hippocampus as well as the deficit in olfactory learning in the Ts65Dn mice. Similar alterations have also been observed in individuals with DS. To determine whether the impairment in adult neurogenesis is, in fact, responsible for the hypocellularity in the hippocampus and physiology of the olfactory bulb, we have analyzed cell proliferation and neuronal maturation in the two major adult neurogenic niches in the Ts656Dn mice: the subgranular zone (SGZ) of the hippocampus and the subventricular zone (SVZ). Additionally, we carried out a study to determine the survival rate and phenotypic fate of newly generated cells in both regions, injecting 5′BrdU and sacrificing the mice 21 days later, and analyzing the number and phenotype of the remaining 5′BrdU-positive cells. We observed a reduction in the number of proliferating (Ki67 positive) cells and immature (doublecortin positive) neurons in the subgranular and SVZ of Ts65Dn mice, but we did not observe changes in the number of surviving cells or in their phenotype. These data correlated with a lower number of apoptotic cells (cleaved caspase 3 positive) in Ts65Dn. We conclude that although adult Ts65Dn mice have a lower number of proliferating cells, it is compensated by a lower level of cell death. This higher survival rate in Ts65Dn produces a final number of mature cells similar to controls. Therefore, the reduction of adult neurogenesis cannot be held responsible for the neuronal hypocellularity in the hippocampus or for the olfactory learning deficit of Ts65Dn mice.

IGF-1 Receptor Differentially Regulates Spontaneous and Evoked Transmission via Mitochondria at Hippocampal Synapses

SummaryThe insulin-like growth factor-1 receptor (IGF-1R) signaling is a key regulator of lifespan, growth, and development. While reduced IGF-1R signaling delays aging and Alzheimer’s disease progression, whether and how it regulates information processing at central synapses remains elusive. Here, we show that presynaptic IGF-1Rs are basally active, regulating synaptic vesicle release and short-term plasticity in excitatory hippocampal neurons. Acute IGF-1R blockade or transient knockdown suppresses spike-evoked synaptic transmission and presynaptic cytosolic Ca2+ transients, while promoting spontaneous transmission and resting Ca2+ level. This dual effect on transmitter release is mediated by mitochondria that attenuate Ca2+ buffering in the absence of spikes and decrease ATP production during spiking activity. We conclude that the mitochondria, activated by IGF-1R signaling, constitute a critical regulator of information processing in hippocampal neurons by maintaining evoked-to-spontaneous transmission ratio, while constraining synaptic facilitation at high frequencies. Excessive IGF-1R tone may contribute to hippocampal hyperactivity associated with Alzheimer’s disease.Video

How to bake a brain: yeast as a model neuron.

More than 30 years ago Dan Koshland published an inspirational essay presenting the bacterium as a model neuron (Koshland, Trends Neurosci 6:133-137, 1983). In the article he argued that there are several similarities between neurons and bacterial cells in "how signals are processed within a cell or how this processing machinery can be modified to produce plasticity". He then explored the bacterial chemosensory system to emphasize its attributes that are analogous to information processing in neurons. In this review, we wish to expand Koshland's original idea by adding the yeast cell to the list of useful models of a neuron. The fact that yeasts and neurons are specialized versions of the eukaryotic cell sharing all principal components sets the stage for a grand evolutionary tinkering where these components are employed in qualitatively different tasks, but following analogous molecular logic. By way of example, we argue that evolutionarily conserved key components involved in polarization processes (from budding or mating in Saccharomyces cervisiae to neurite outgrowth or spinogenesis in neurons) are shared between yeast and neurons. This orthologous conservation of modules makes S. cervisiae an excellent model organism to investigate neurobiological questions. We substantiate this claim by providing examples of yeast models used for studying neurological diseases.

Reliability of weak signals detection in neurons with noise

Previous experimental and theoretical studies have demonstrated that a weak signal can be amplified and optimized by the assistance of noise. The response of the system undergoes stochastic resonance (SR) like behavior. The underlying mechanisms are fairly simple and robust. This phenomenon has been observed in a large variety of systems, including physical and biological systems. In the nervous system, the majority of synaptic input is too weak to make neurons fire a spike. This weak (or subthreshold) signals detection is very important for animal survival, and pulse detection is a simple but basic task of neuronal information transmission and processing. Some studies have found that subthreshold signals can be transmitted by the application of external noise. However, neurons are subjected to various kinds of inherent noise. Recently, theoretical work has revealed that this inherent noise improves signals detection ability. The detection ability of a single neuron is limited, and the neuronal circuit can perform this task very well by detecting the synchronization of presynaptic potentials. Here, we review recent studies of subthreshold detection by both single neurons and neuronal circuits.

Spiking Activity of a LIF Neuron in Distributed Delay Framework

Evolution of membrane potential and spiking activity for a single leaky integrate-and-fire (LIF) neuron in distributed delay framework (DDF) is investigated. DDF provides a mechanism to incorporate memory element in terms of delay (kernel) function into a single neuron models. This investigation includes LIF neuron model with two different kinds of delay kernel functions, namely, gamma distributed delay kernel function and hypo-exponential distributed delay kernel function. Evolution of membrane potential for considered models is studied in terms of stationary state probability distribution (SPD). Stationary state probability distribution of membrane potential (SPDV) for considered neuron models are found asymptotically similar which is Gaussian distributed. In order to investigate the effect of membrane potential delay, rate code scheme for neuronal information processing is applied. Firing rate and Fano-factor for considered neuron models are calculated and standard LIF model is used for comparative study. It is noticed that distributed delay increases the spiking activity of a neuron. Increase in spiking activity of neuron in DDF is larger for hypo-exponential distributed delay function than gamma distributed delay function. Moreover, in case of hypo-exponential delay function, a LIF neuron generates spikes with Fano-factor less than 1.

NF-kappaB Signaling Pathways in Neurological Inflammation: A Mini Review.

The NF-κB (nuclear factor κ-light-chain-enhancer of activated B cells) transcription factor family is a pleiotropic regulator of many cellular signaling pathways, providing a mechanism for the cells in response to a wide variety of stimuli linking to inflammation. The stimulated cells will be regulated by not only the canonical but also non-canonical NF-κB pathways. To initiate both of these pathways, IκB-degradation triggers NF-κB release and the nuclear translocated-heterodimer (or homodimer) can associate with the κB sites of promoter to regulate the gene transcriptions. NF-κB ubiquitously expresses in neurons and the constitutive NF-κB activation is associated with processing of neuronal information. NF-κB can regulate the transcription of genes such as chemokines, cytokines, proinflammatory enzymes, adhesion molecules, proinflammatory transcription factors, and other factors to modulate the neuronal survival. In neuronal insult, NF-κB constitutively active in neuron cell bodies can protect neurons against different injuries and regulate the neuronal inflammatory reactions. Besides neurons, NF-κB transcription factors are abundant in glial cells and cerebral blood vessels and the diverse functions of NF-κB also regulate the inflammatory reaction around the neuronal environment. NF-κB transcription factors are abundant in the brain and exhibit diverse functions. Several central nerve system (CNS) diseases are linked to NF-κB activated by inflammatory mediators. The RelA and c-Rel expression produce opposite effects on neuronal survival. Importantly, c-Rel expression in CNS plays a critical role in anti-apoptosis and reduces the age-related behaviors. Moreover, the different subunits of NF-κB dimer formation can modulate the neuroninflammation, neuronal protection, or neurotoxicity. The diverse functions of NF-κB depend on the subunits of the NF-κB dimer-formation which enable us to develop a therapeutic approach to neuroinflammation based on a new concept of inflammation as a strategic tool in neuronal cells. However, the detail role of NF-κB in neuroinflammation, remains to be clarified. In the present article, we provide an updated review of the current state of our knowledge about relationship between NF-κB and neuroinflammation.

Visual Stimuli Evoked Action Potentials Trigger Rapidly Propagating Dendritic Calcium Transients in the Frog Optic Tectum Layer 6 Neurons.

The superior colliculus in mammals or the optic tectum in amphibians is a major visual information processing center responsible for generation of orientating responses such as saccades in monkeys or prey catching avoidance behavior in frogs. The conserved structure function of the superior colliculus the optic tectum across distant species such as frogs, birds monkeys permits to draw rather general conclusions after studying a single species. We chose the frog optic tectum because we are able to perform whole-cell voltage-clamp recordings fluorescence imaging of tectal neurons while they respond to a visual stimulus. In the optic tectum of amphibians most visual information is processed by pear-shaped neurons possessing long dendritic branches, which receive the majority of synapses originating from the retinal ganglion cells. Since the first step of the retinal input integration is performed on these dendrites, it is important to know whether this integration is enhanced by active dendritic properties. We demonstrate that rapid calcium transients coinciding with the visual stimulus evoked action potentials in the somatic recordings can be readily detected up to the fine branches of these dendrites. These transients were blocked by calcium channel blockers nifedipine CdCl2 indicating that calcium entered dendrites via voltage-activated L-type calcium channels. The high speed of calcium transient propagation, >300 μm in <10 ms, is consistent with the notion that action potentials, actively propagating along dendrites, open voltage-gated L-type calcium channels causing rapid calcium concentration transients in the dendrites. We conclude that such activation by somatic action potentials of the dendritic voltage gated calcium channels in the close vicinity to the synapses formed by axons of the retinal ganglion cells may facilitate visual information processing in the principal neurons of the frog optic tectum.

Postmating Circuitry Modulates Salt Taste Processing to Increase Reproductive Output in Drosophila

To optimize survival and reproduction, animals must match their nutrient intake to their current needs. Reproduction profoundly changes nutritional requirements, with many species showing an appetite for sodium during reproductive periods. How this internal state modifies neuronal information processing to ensure homeostasis is not understood. Here, we show that dietary sodium levels positively affect reproductive output in Drosophila melanogaster; to satisfy this requirement, females develop a strong, specific appetite for sodium following mating. We show that mating modulates gustatory processing to increase the probability of initiating feeding on salt. This postmating effect is not due to salt depletion by egg production, since abolishing egg production leaves the sodium appetite intact. Rather, the salt appetite is induced need-independently by male-derived Sex Peptide acting on the Sex Peptide Receptor in female reproductive tract neurons. Wefurther demonstrate that postmating appetites for both salt and yeast are driven by the resultant silencing of downstream SAG neurons. Surprisingly, unlike the postmating yeast appetite, the salt appetite does not require octopamine, suggesting a divergence in the postmating circuitry. These findings demonstrate that the postmating circuit supports reproduction by increasing the palatability of specific nutrients. Such a feedforward regulation of sensory processing may represent a common mechanism through which reproductive state-sensitive circuits modify complex behaviors across species.

Dendritic and Axonal Architecture of Individual Pyramidal Neurons across Layers of Adult Human Neocortex.

The size and shape of dendrites and axons are strong determinants of neuronal information processing. Our knowledge on neuronal structure and function is primarily based on brains of laboratory animals. Whether it translates to human is not known since quantitative data on “full” human neuronal morphologies are lacking. Here, we obtained human brain tissue during resection surgery and reconstructed basal and apical dendrites and axons of individual neurons across all cortical layers in temporal cortex (Brodmann area 21). Importantly, morphologies did not correlate to etiology, disease severity, or disease duration. Next, we show that human L(ayer) 2 and L3 pyramidal neurons have 3-fold larger dendritic length and increased branch complexity with longer segments compared with temporal cortex neurons from macaque and mouse. Unsupervised cluster analysis classified 88% of human L2 and L3 neurons into human-specific clusters distinct from mouse and macaque neurons. Computational modeling of passive electrical properties to assess the functional impact of large dendrites indicates stronger signal attenuation of electrical inputs compared with mouse. We thus provide a quantitative analysis of “full” human neuron morphologies and present direct evidence that human neurons are not “scaled-up” versions of rodent or macaque neurons, but have unique structural and functional properties.

Diverse impact of acute and long-term extracellular proteolytic activity on plasticity of neuronal excitability.

Learning and memory require alteration in number and strength of existing synaptic connections. Extracellular proteolysis within the synapses has been shown to play a pivotal role in synaptic plasticity by determining synapse structure, function, and number. Although synaptic plasticity of excitatory synapses is generally acknowledged to play a crucial role in formation of memory traces, some components of neural plasticity are reflected by nonsynaptic changes. Since information in neural networks is ultimately conveyed with action potentials, scaling of neuronal excitability could significantly enhance or dampen the outcome of dendritic integration, boost neuronal information storage capacity and ultimately learning. However, the underlying mechanism is poorly understood. With this regard, several lines of evidence and our most recent study support a view that activity of extracellular proteases might affect information processing in neuronal networks by affecting targets beyond synapses. Here, we review the most recent studies addressing the impact of extracellular proteolysis on plasticity of neuronal excitability and discuss how enzymatic activity may alter input-output/transfer function of neurons, supporting cognitive processes. Interestingly, extracellular proteolysis may alter intrinsic neuronal excitability and excitation/inhibition balance both rapidly (time of minutes to hours) and in long-term window. Moreover, it appears that by cleavage of extracellular matrix (ECM) constituents, proteases may modulate function of ion channels or alter inhibitory drive and hence facilitate active participation of dendrites and axon initial segments (AISs) in adjusting neuronal input/output function. Altogether, a picture emerges whereby both rapid and long-term extracellular proteolysis may influence some aspects of information processing in neurons, such as initiation of action potential, spike frequency adaptation, properties of action potential and dendritic backpropagation.

Energy Efficient Neurons With Generalized Inverse Gaussian Conditional and Marginal Hitting Times

Neuronal information processing is energetically costly. Energy supply restrictions on information processing have resulted in the evolution of brains to compute and communicate information with remarkable energy efficiency. Indeed, energy minimization subject to functional constraints is a unifying principle. Toward better comprehension of neuronal information processing and communication from an information-energy standpoint, we consider a continuous time, continuous state-space neuron model with a generalized inverse Gaussian (GIG) conditional density. This GIG model arises from a Levy diffusion that contains both homogeneous Poisson processes and Wiener processes with drift as special cases. We show that, when the energy constraints consist of a tripartite family apropos of the GIG model, the distribution of input excitation, $\Lambda $ , that maximizes bits per Joule (bpJ) generates an output interspike interval duration $T$ that possesses a related GIG marginal distribution. Most importantly, we obtain the exact expression for the bpJ-maximizing distribution of $\Lambda $ in terms of Bessel functions that are readily evaluated numerically. This permits display of the strictly concave curves of bpJ-maximized mutual information $I(\Lambda ;T)$ . Because bpJ equals bits per second/watt, these curves serve as the Shannon-theory capacity v. power curves for GIG neuron models. We show that the noise in GIG channels is essentially multiplicative, so our results may have significance for broader classes of fading channels.

Glial Glycolysis Is Essential for Neuronal Survival in Drosophila

Neuronal information processing requires a large amount of energy, indicating that sugars and other metabolites must be efficiently delivered. However, reliable neuronal function also depends on the maintenance of a constant microenvironment in the brain. Therefore, neurons are efficiently separated from circulation by the blood-brain barrier, and their long axons are insulated by glial processes. At the example of the Drosophila brain, we addressed how sugar is shuttled across the barrier to nurture neurons. We show that glial cells of the blood-brain barrier specifically take up sugars and that their metabolism relies on glycolysis, which, surprisingly, is dispensable in neurons. Glial cells secrete alanine and lactate to fuel neuronal mitochondria, and lack of glial glycolysis specifically in the adult brain causes neurodegeneration. Our work implies that a global metabolic compartmentalization and coupling of neurons and glial cells is a conserved, fundamental feature of bilaterian nervous systems independent of their size.

Emergence of Slow-Switching Assemblies in Structured Neuronal Networks.

Unraveling the interplay between connectivity and spatio-temporal dynamics in neuronal networks is a key step to advance our understanding of neuronal information processing. Here we investigate how particular features of network connectivity underpin the propensity of neural networks to generate slow-switching assembly (SSA) dynamics, i.e., sustained epochs of increased firing within assemblies of neurons which transition slowly between different assemblies throughout the network. We show that the emergence of SSA activity is linked to spectral properties of the asymmetric synaptic weight matrix. In particular, the leading eigenvalues that dictate the slow dynamics exhibit a gap with respect to the bulk of the spectrum, and the associated Schur vectors exhibit a measure of block-localization on groups of neurons, thus resulting in coherent dynamical activity on those groups. Through simple rate models, we gain analytical understanding of the origin and importance of the spectral gap, and use these insights to develop new network topologies with alternative connectivity paradigms which also display SSA activity. Specifically, SSA dynamics involving excitatory and inhibitory neurons can be achieved by modifying the connectivity patterns between both types of neurons. We also show that SSA activity can occur at multiple timescales reflecting a hierarchy in the connectivity, and demonstrate the emergence of SSA in small-world like networks. Our work provides a step towards understanding how network structure (uncovered through advancements in neuroanatomy and connectomics) can impact on spatio-temporal neural activity and constrain the resulting dynamics.

Anatomy and physiology of the thick-tufted layer 5 pyramidal neuron.

The thick-tufted layer 5 (TTL5) pyramidal neuron is one of the most extensively studied neuron types in the mammalian neocortex and has become a benchmark for understanding information processing in excitatory neurons. By virtue of having the widest local axonal and dendritic arborization, the TTL5 neuron encompasses various local neocortical neurons and thereby defines the dimensions of neocortical microcircuitry. The TTL5 neuron integrates input across all neocortical layers and is the principal output pathway funneling information flow to subcortical structures. Several studies over the past decades have investigated the anatomy, physiology, synaptology, and pathophysiology of the TTL5 neuron. This review summarizes key discoveries and identifies potential avenues of research to facilitate an integrated and unifying understanding on the role of a central neuron in the neocortex.

Membrane-derived phospholipids control synaptic neurotransmission and plasticity.

Synaptic communication is a dynamic process that is key to the regulation of neuronal excitability and information processing in the brain. To date, however, the molecular signals controlling synaptic dynamics have been poorly understood. Membrane-derived bioactive phospholipids are potential candidates to control short-term tuning of synaptic signaling, a plastic event essential for information processing at both the cellular and neuronal network levels in the brain. Here, we showed that phospholipids affect excitatory and inhibitory neurotransmission by different degrees, loci, and mechanisms of action. Signaling triggered by lysophosphatidic acid (LPA) evoked rapid and reversible depression of excitatory and inhibitory postsynaptic currents. At excitatory synapses, LPA-induced depression depended on LPA1/Gαi/o-protein/phospholipase C/myosin light chain kinase cascade at the presynaptic site. LPA increased myosin light chain phosphorylation, which is known to trigger actomyosin contraction, and reduced the number of synaptic vesicles docked to active zones in excitatory boutons. At inhibitory synapses, postsynaptic LPA signaling led to dephosphorylation, and internalization of the GABAAγ2 subunit through the LPA1/Gα12/13-protein/RhoA/Rho kinase/calcineurin pathway. However, LPA-induced depression of GABAergic transmission was correlated with an endocytosis-independent reduction of GABAA receptors, possibly by GABAAγ2 dephosphorylation and subsequent increased lateral diffusion. Furthermore, endogenous LPA signaling, mainly via LPA1, mediated activity-dependent inhibitory depression in a model of experimental synaptic plasticity. Finally, LPA signaling, most likely restraining the excitatory drive incoming to motoneurons, regulated performance of motor output commands, a basic brain processing task. We propose that lysophospholipids serve as potential local messengers that tune synaptic strength to precedent activity of the neuron.

A reliable model for gamma oscillations in hippocampal tissue.

Gamma oscillations (30-100 Hz) reflect a fast brain rhythm that provides a fundamental mechanism of complex neuronal information processing in the hippocampus and in the neocortex in vivo. Gamma oscillations have been implicated in higher brain functions, such as sensory perception, motor activity, and memory formation. Experimental studies on synaptic transmission and bioenergetics underlying gamma oscillations have primarily used acute slices of the hippocampus. This study tests whether organotypic hippocampal slice cultures of the rat provide an alternative model for cortical gamma oscillations in vitro. Our findings are that 1) slice cultures feature well-preserved laminated architecture and neuronal morphology; 2) slice cultures of different maturation stages (7-28 days in vitro) reliably express gamma oscillations at about 40 Hz as induced by cholinergic (acetylcholine) or glutamatergic (kainate) receptor agonists; 3) the peak frequency of gamma oscillations depends on the temperature, with an increase of ∼ 3.5 Hz per degree Celsius for the range of 28-36 °C; 4) most slice cultures show persistent gamma oscillations for ∼ 1 hr during electrophysiological local field potential recordings, and later alterations may occur; and 5) in slice cultures, glucose at a concentration of 5 mM in the recording solution is sufficient to power gamma oscillations, and additional energy substrate supply with monocarboxylate metabolite lactate (2 mM) exclusively increases the peak frequency by ∼ 4 Hz. This study shows that organotypic hippocampal slice cultures provide a reliable model to study agonist-induced gamma oscillations at glucose levels near the physiological range.