Variance analysis as a method to predict the locus of plasticity at populations of non-uniform synapses.

Our knowledge on synaptic transmission in the central nervous system has often been obtained by evoking synaptic responses to populations of synapses. Analysis of the variance in synaptic responses can be applied as a method to predict whether a change in synaptic responses is a consequence of altered presynaptic neurotransmitter release or postsynaptic receptors. However, variance analysis is based on binomial statistics, which assumes that synapses are uniform. In reality, synapses are far from uniform, which questions the reliability of variance analysis when applying this method to populations of synapses. To address this, we used an in silico model for evoked synaptic responses and compared variance analysis outcomes between populations of uniform versus non-uniform synapses. This simulation revealed that variance analysis produces similar results irrespectively of the grade of uniformity of synapses. We put this variance analysis to the test with an electrophysiology experiment using a model system for which the loci of plasticity are well established: the effect of amyloid-ß on synapses. Variance analysis correctly predicted that postsynaptically produced amyloid-ß triggered predominantly a loss of synapses and a minor reduction of postsynaptic currents in remaining synapses with little effect on presynaptic release probability. We propose that variance analysis can be reliably used to predict the locus of synaptic changes for populations of non-uniform synapses.

Variance analysis as a tool to predict the mechanism underlying synaptic plasticity.

BACKGROUND: The strength of synaptic transmission onto a neuron depends on the number of functional vesicle release sites (N), the probability of vesicle release (Pr), and the quantal size (Q). Statistical tools based on the quantal model of synaptic transmission can be used to acquire information on which of these parameters is the source of plasticity. However, quantal analysis depends on assumptions that may not be met at central synapses. NEW METHOD: We examined the merit of quantal analysis to extract the mechanisms underlying synaptic plasticity by applying binomial statistics on the variance in amplitude of postsynaptic currents evoked at Schaffer collateral-CA1 (Sc-CA1) synapses in mouse hippocampal slices. We extend this analysis by combining the conventional inverse square of the coefficient of variation (1/CV2) with the variance-to-mean ratio (VMR). RESULTS: This method can be used to assess the relative, but not absolute, contribution of N, Pr and Q to synaptic plasticity. The changes in 1/CV2 and VMR values correctly reflect experimental modifications of N, Pr and Q at Sc-CA1 synapses. COMPARISON WITH EXISTING METHODS: While the 1/CV2 depends on N and Pr, but is independent of Q, the VMR is dependent on Pr and Q, but not on N. Combining both allows for a rapid assessment of the mechanism underlying synaptic plasticity without the need for additional electrophysiological experiments. CONCLUSION: Combining the 1/CV2 with the VMR allows for a reliable prediction of the relative contribution of changes in N, Pr and Q to synaptic plasticity.

Synaptic plasticity through activation of GluA3-containing AMPA-receptors.

Excitatory synaptic transmission is mediated by AMPA-type glutamate receptors (AMPARs). In CA1 pyramidal neurons of the hippocampus two types of AMPARs predominate: those that contain subunits GluA1 and GluA2 (GluA1/2), and those that contain GluA2 and GluA3 (GluA2/3). Whereas subunits GluA1 and GluA2 have been extensively studied, the contribution of GluA3 to synapse physiology has remained unclear. Here we show in mice that GluA2/3s are in a low-conductance state under basal conditions, and although present at synapses they contribute little to synaptic currents. When intracellular cyclic AMP (cAMP) levels rise, GluA2/3 channels shift to a high-conductance state, leading to synaptic potentiation. This cAMP-driven synaptic potentiation requires the activation of both protein kinase A (PKA) and the GTPase Ras, and is induced upon the activation of ß-adrenergic receptors. Together, these experiments reveal a novel type of plasticity at CA1 hippocampal synapses that is expressed by the activation of GluA3-containing AMPARs.

A basal ganglia circuit for evaluating action outcomes.

The basal ganglia, a group of subcortical nuclei, play a crucial role in decision-making by selecting actions and evaluating their outcomes. While much is known about the function of the basal ganglia circuitry in selection, how these nuclei contribute to outcome evaluation is less clear. Here we show that neurons in the habenula-projecting globus pallidus (GPh) in mice are essential for evaluating action outcomes and are regulated by a specific set of inputs from the basal ganglia. We find in a classical conditioning task that individual mouse GPh neurons bidirectionally encode whether an outcome is better or worse than expected. Mimicking these evaluation signals with optogenetic inhibition or excitation is sufficient to reinforce or discourage actions in a decision-making task. Moreover, cell-type-specific synaptic manipulations reveal that the inhibitory and excitatory inputs to the GPh are necessary for mice to appropriately evaluate positive and negative feedback, respectively. Finally, using rabies-virus-assisted monosynaptic tracing, we show that the GPh is embedded in a basal ganglia circuit wherein it receives inhibitory input from both striosomal and matrix compartments of the striatum, and excitatory input from the 'limbic' regions of the subthalamic nucleus. Our results provide evidence that information about the selection and evaluation of actions is channelled through distinct sets of basal ganglia circuits, with the GPh representing a key locus in which information of opposing valence is integrated to determine whether action outcomes are better or worse than expected.

Glutamatergic synaptic plasticity in the mesocorticolimbic system in addiction.

Addictive drugs remodel the brain's reward circuitry, the mesocorticolimbic dopamine (DA) system, by inducing widespread adaptations of glutamatergic synapses. This drug-induced synaptic plasticity is thought to contribute to both the development and the persistence of addiction. This review highlights the synaptic modifications that are induced by in vivo exposure to addictive drugs and describes how these drug-induced synaptic changes may contribute to the different components of addictive behavior, such as compulsive drug use despite negative consequences and relapse. Initially, exposure to an addictive drug induces synaptic changes in the ventral tegmental area (VTA). This drug-induced synaptic potentiation in the VTA subsequently triggers synaptic changes in downstream areas of the mesocorticolimbic system, such as the nucleus accumbens (NAc) and the prefrontal cortex (PFC), with further drug exposure. These glutamatergic synaptic alterations are then thought to mediate many of the behavioral symptoms that characterize addiction. The later stages of glutamatergic synaptic plasticity in the NAc and in particular in the PFC play a role in maintaining addiction and drive relapse to drug-taking induced by drug-associated cues. Remodeling of PFC glutamatergic circuits can persist into adulthood, causing a lasting vulnerability to relapse. We will discuss how these neurobiological changes produced by drugs of abuse may provide novel targets for potential treatment strategies for addiction.