Adenosine Differentially Modulates Synaptic Transmission of Excitatory and Inhibitory Microcircuits in Layer 4 of Rat Barrel Cortex.

Adenosine is considered to be a key regulator of sleep homeostasis by promoting slow-wave sleep through inhibition of the brain's arousal centers. However, little is known about the effect of adenosine on neuronal network activity at the cellular level in the neocortex. Here, we show that adenosine differentially modulates synaptic transmission between different types of neurons in cortical layer 4 (L4) through activation of pre- and/or postsynaptically located adenosine A1 receptors. In recurrent excitatory connections between L4 spiny neurons, adenosine suppresses synaptic transmission through activation of both pre- and postsynaptic A1 receptors. In reciprocal excitatory and inhibitory connections between L4 spiny neurons and interneurons, adenosine strongly suppresses excitatory transmission via activating presynaptic A1 receptors but only slightly suppresses inhibitory transmission via activating postsynaptic A1 receptors. Adenosine has no effect on inhibitory transmission between L4 interneurons. The effect of adenosine is concentration dependent and first visible at a concentration of 1 µM. The effect of adenosine is blocked by the specific A1 receptor antagonist, 8-cyclopentyltheophylline or the nonspecific adenosine receptor antagonist, caffeine. By differentially affecting excitatory and inhibitory synaptic transmission, adenosine changes the excitation-inhibition balance and causes an overall shift to lower excitability in L4 primary somatosensory (barrel) cortical microcircuits.

Cell type-specific effects of adenosine on cortical neurons.

The neuromodulator adenosine is widely considered to be a key regulator of sleep homeostasis and an indicator of sleep need. Although the effect of adenosine on subcortical areas has been previously described, the effects on cortical neurons have not been addressed systematically to date. To that purpose, we performed in vitro whole-cell patch-clamp recordings and biocytin staining of pyramidal neurons and interneurons throughout all layers of rat prefrontal and somatosensory cortex, followed by morphological analysis. We found that adenosine, via the A1 receptor, exerts differential effects depending on neuronal cell type and laminar location. Interneurons and pyramidal neurons in layer 2 and a subpopulation of layer 3 pyramidal neurons that displayed regular spiking were insensitive to adenosine application, whereas other pyramidal cells in layers 3-6 were hyperpolarized (range 1.2-10.8 mV). Broad tufted pyramidal neurons with little spike adaptation showed a small adenosine response, whereas slender tufted pyramidal neurons with substantial adaptation showed a bigger response. These studies of the action of adenosine at the postsynaptic level may contribute to the understanding of the changes in cortical circuit functioning that take place between sleep and awakening.

Morphological and physiological characterization of pyramidal neuron subtypes in rat medial prefrontal cortex.

The medial prefrontal cortex (mPFC) has been implicated in cognitive and executive processes including decision making, working memory and behavioral flexibility. Cortical processing depends on the interaction between distinct neuronal cell types in different cortical layers. To better understand cortical processing in the rat mPFC, we studied the diversity of pyramidal neurons using in vitro whole-cell patch clamp recordings and biocytin staining of neurons, followed by morphological analysis. Using unsupervised cluster analysis for the objective grouping of neurons, we identified more than 10 different pyramidal subtypes spread across the different cortical layers. Layer 2 pyramidal neurons possessed a unique morphology with wide apical dendritic field spans and a narrow basal field span. Layer 3 contained the only subtype that showed a burst of action potentials upon current injection. Layer 5 pyramidal neurons showed the largest voltage sags. Finally, pyramidal neurons in layer 6 (L6) showed a great variety in their morphology with 39% of L6 neurons possessing tall apical dendrites that extend into layer 1. Future experiments on the functional role of the mPFC should take into account the great diversity of pyramidal neurons.

Inter-network interactions: impact of connections between oscillatory neuronal networks on oscillation frequency and pattern.

Oscillations in electrical activity are a characteristic feature of many brain networks and display a wide variety of temporal patterns. A network may express a single oscillation frequency, alternate between two or more distinct frequencies, or continually express multiple frequencies. In addition, oscillation amplitude may fluctuate over time. The origin of this complex repertoire of activity remains unclear. Different cortical layers often produce distinct oscillation frequencies. To investigate whether interactions between different networks could contribute to the variety of oscillation patterns, we created two model networks, one generating on its own a relatively slow frequency (20 Hz; slow network) and one generating a fast frequency (32 Hz; fast network). Taking either the slow or the fast network as source network projecting connections to the other, or target, network, we systematically investigated how type and strength of inter-network connections affected target network activity. For high inter-network connection strengths, we found that the slow network was more effective at completely imposing its rhythm on the fast network than the other way around. The strongest entrainment occurred when excitatory cells of the slow network projected to excitatory or inhibitory cells of the fast network. The fast network most strongly imposed its rhythm on the slow network when its excitatory cells projected to excitatory cells of the slow network. Interestingly, for lower inter-network connection strengths, multiple frequencies coexisted in the target network. Just as observed in rat prefrontal cortex, the target network could express multiple frequencies at the same time, alternate between two distinct oscillation frequencies, or express a single frequency with alternating episodes of high and low amplitude. Together, our results suggest that input from other oscillating networks may markedly alter a network's frequency spectrum and may partly be responsible for the rich repertoire of temporal oscillation patterns observed in the brain.

External drive to inhibitory cells induces alternating episodes of high- and low-amplitude oscillations.

Electrical oscillations in neuronal network activity are ubiquitous in the brain and have been associated with cognition and behavior. Intriguingly, the amplitude of ongoing oscillations, such as measured in EEG recordings, fluctuates irregularly, with episodes of high amplitude alternating with episodes of low amplitude. Despite the widespread occurrence of amplitude fluctuations in many frequency bands and brain regions, the mechanisms by which they are generated are poorly understood. Here, we show that irregular transitions between sub-second episodes of high- and low-amplitude oscillations in the alpha/beta frequency band occur in a generic neuronal network model consisting of interconnected inhibitory and excitatory cells that are externally driven by sustained cholinergic input and trains of action potentials that activate excitatory synapses. In the model, we identify the action potential drive onto inhibitory cells, which represents input from other brain areas and is shown to desynchronize network activity, to be crucial for the emergence of amplitude fluctuations. We show that the duration distributions of high-amplitude episodes in the model match those observed in rat prefrontal cortex for oscillations induced by the cholinergic agonist carbachol. Furthermore, the mean duration of high-amplitude episodes varies in a bell-shaped manner with carbachol concentration, just as in mouse hippocampus. Our results suggest that amplitude fluctuations are a general property of oscillatory neuronal networks that can arise through background input from areas external to the network.

Fast network oscillations in vitro exhibit a slow decay of temporal auto-correlations.

Ongoing neuronal oscillations in vivo exhibit non-random amplitude fluctuations as reflected in a slow decay of temporal auto-correlations that persist for tens of seconds. Interestingly, the decay of auto-correlations is altered in several brain-related disorders, including epilepsy, depression and Alzheimer's disease, suggesting that the temporal structure of oscillations depends on intact neuronal networks in the brain. Whether structured amplitude modulation occurs only in the intact brain or whether isolated neuronal networks can also give rise to amplitude modulation with a slow decay is not known. Here, we examined the temporal structure of cholinergic fast network oscillations in acute hippocampal slices. For the first time, we show that a slow decay of temporal correlations can emerge from synchronized activity in isolated hippocampal networks from mice, and is maximal at intermediate concentrations of the cholinergic agonist carbachol. Using zolpidem, a positive allosteric modulator of GABA(A) receptor function, we found that increased inhibition leads to longer oscillation bursts and more persistent temporal correlations. In addition, we asked if these findings were unique for mouse hippocampus, and we therefore analysed cholinergic fast network oscillations in rat prefrontal cortex slices. We observed significant temporal correlations, which were similar in strength to those found in mouse hippocampus and human cortex. Taken together, our data indicate that fast network oscillations with temporal correlations can be induced in isolated networks in vitro in different species and brain areas, and therefore may serve as model systems to investigate how altered temporal correlations in disease may be rescued with pharmacology.

Flexible spike timing of layer 5 neurons during dynamic beta oscillation shifts in rat prefrontal cortex.

Human brain oscillations occur in different frequency bands that have been linked to different behaviours and cognitive processes. Even within specific frequency bands such as the beta- (14-30 Hz) or gamma-band (30-100 Hz), oscillations fluctuate in frequency and amplitude. Such frequency fluctuations most probably reflect changing states of neuronal network activity, as brain oscillations arise from the correlated synchronized activity of large numbers of neurons. However, the neuronal mechanisms governing the dynamic nature of amplitude and frequency fluctuations within frequency bands remain elusive. Here we show that in acute slices of rat prefrontal cortex (PFC), carbachol-induced oscillations in the beta-band show frequency and amplitude fluctuations. Fast and slow non-harmonic frequencies are distributed differentially over superficial and deep cortical layers, with fast frequencies being present in layer 3, while layer 6 only showed slow oscillation frequencies. Layer 5 pyramidal cells and interneurons experience both fast and slow frequencies and they time their spiking with respect to the dominant frequency. Frequency and phase information is encoded and relayed in the layer 5 network through timed excitatory and inhibitory synaptic transmission. Our data indicate that frequency fluctuations in the beta-band reflect synchronized activity in different cortical subnetworks, that both influence spike timing of output layer 5 neurons. Thus, amplitude and frequency fluctuations within frequency bands may reflect activity in distinct cortical neuronal subnetworks that may process information in a parallel fashion.

Prelimbic and infralimbic prefrontal cortex interact during fast network oscillations.

BACKGROUND: The medial prefrontal cortex has been implicated in a variety of cognitive and executive processes such as decision making and working memory. The medial prefrontal cortex of rodents consists of several areas including the prelimbic and infralimbic cortex that are thought to be involved in different aspects of cognitive performance. Despite the distinct roles in cognitive behavior that have been attributed to prelimbic and infralimbic cortex, little is known about neuronal network functioning of these areas, and whether these networks show any interaction during fast network oscillations. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that fast network oscillations in rat infralimbic cortex slices occur at higher frequencies and with higher power than oscillations in prelimbic cortex. The difference in oscillation frequency disappeared when prelimbic and infralimbic cortex were disconnected. CONCLUSIONS/SIGNIFICANCE: Our data indicate that neuronal networks of prelimbic and infralimbic cortex can sustain fast network oscillations independent of each other, but suggest that neuronal networks of prelimbic and infralimbic cortex are interacting during these oscillations.

Proteolytic processing of the receptor-type protein tyrosine phosphatase PTPBR7.

The single-copy mouse gene Ptprr gives rise to different protein tyrosine phosphatase (PTP) isoforms in neuronal cells through the use of distinct promoters, alternative splicing, and multiple translation initiation sites. Here, we examined the array of post-translational modifications imposed on the PTPRR protein isoforms PTPBR7, PTP-SL, PTPPBSgamma42 and PTPPBSgamma37, which have distinct N-terminal segments and localize to different parts of the cell. All isoforms were found to be short-lived, constitutively phosphorylated proteins. In addition, the transmembrane isoform, PTPBR7, was subject to N-terminal proteolytic processing, in between amino acid position 136 and 137, resulting in an additional, 65-kDa transmembrane PTPRR isoform. Unlike for some other receptor-type PTPs, the proteolytically produced N-terminal ectodomain does not remain associated with this PTPRR-65. Shedding of PTPBR7-derived polypeptides at the cell surface further adds to the molecular complexity of PTPRR biology.

Nicotinic modulation of neuronal networks: from receptors to cognition.

RATIONALE: Nicotine affects many aspects of human cognition, including attention and memory. Activation of nicotinic acetylcholine receptors (nAChRs) in neuronal networks modulates activity and information processing during cognitive tasks, which can be observed in electroencephalograms (EEGs) and functional magnetic resonance imaging studies. OBJECTIVES: In this review, we will address aspects of nAChR functioning as well as synaptic and cellular modulation important for nicotinic impact on neuronal networks that ultimately underlie its effects on cognition. Although we will focus on general mechanisms, an emphasis will be put on attention behavior and nicotinic modulation of prefrontal cortex. In addition, we will discuss how nicotinic effects at the neuronal level could be related to its effects on the cognitive level through the study of electrical oscillations as observed in EEGs and brain slices. RESULTS/CONCLUSIONS: Very little is known about mechanisms of how nAChR activation leads to a modification of electrical oscillation frequencies in EEGs. The results of studies using pharmacological interventions and transgenic animals implicate some nAChR types in aspects of cognition, but neuronal mechanisms are only poorly understood. We are only beginning to understand how nAChR distribution in neuronal networks impacts network functioning. Unveiling receptor and neuronal mechanisms important for nicotinic modulation of cognition will be instrumental for treatments of human disorders in which cholinergic signaling have been implicated, such as schizophrenia, attention deficit/hyperactivity disorder, and addiction.

Trophic support delays but does not prevent cell-intrinsic degeneration of neurons deficient for munc18-1.

The stability of neuronal networks is thought to depend on synaptic transmission which provides activity-dependent maintenance signals for both synapses and neurons. Here, we tested the relationship between presynaptic secretion and neuronal maintenance using munc18-1-null mutant mice as a model. These mutants have a specific defect in secretion from synaptic and large dense-cored vesicles [Verhage et al. (2000), Science, 287, 864-869; Voets et al. (2001), Neuron, 31, 581-591]. Neuronal networks in these mutants develop normally up to synapse formation but eventually degenerate. The proposed relationship between secretion and neuronal maintenance was tested in low-density and organotypic cultures and, in vivo, by conditional cell-specific inactivation of the munc18-1 gene. Dissociated munc18-1-deficient neurons died within 4 days in vitro (DIV). Application of trophic factors, insulin or BDNF delayed degeneration up to 7 DIV. In organotypic cultures, munc18-1-deficient neurons survived until 9 DIV. On glial feeders, these neurons survived up to 10 DIV and 14 DIV when insulin was applied. Co-culturing dissociated mutant neurons with wild-type neurons did not prolong survival beyond 4 DIV, but coculturing mutant slices with wild-type slices prolonged survival up to 19 DIV. Cell-specific deletion of munc18-1 expression in cerebellar Purkinje cells in vivo resulted in the specific loss of these neurons without affecting connected or surrounding neurons. Together, these data allow three conclusions. First, the lack of synaptic activity cannot explain the degeneration in munc18-1-null mutants. Second, trophic support delays but cannot prevent degeneration. Third, a cell-intrinsic yet unknown function of munc18-1 is essential for prolonged survival.