Information is stored in neural circuits through long-lasting changes in synaptic strengths. Most studies of information storage have focused on mechanisms such as long-term potentiation and depression (LTP and LTD), in which synaptic strengths change in a synapse-specific manner. In contrast, little attention has been paid to mechanisms that regulate the total synaptic strength of a neuron. Here we describe a new form of synaptic plasticity that increases or decreases the strength of all of a neuron's synaptic inputs as a function of activity. Chronic blockade of cortical culture activity increased the amplitude of miniature excitatory postsynaptic currents (mEPSCs) without changing their kinetics. Conversely, blocking GABA (gamma-aminobutyric acid)-mediated inhibition initially raised firing rates, but over a 48-hour period mESPC amplitudes decreased and firing rates returned to close to control values. These changes were at least partly due to postsynaptic alterations in the response to glutamate, and apparently affected each synapse in proportion to its initial strength. Such 'synaptic scaling' may help to ensure that firing rates do not become saturated during developmental changes in the number and strength of synaptic inputs, as well as stabilizing synaptic strengths during Hebbian modification and facilitating competition between synapses.

How different is local cortical circuitry from a random network? To answer this question, we probed synaptic connections with several hundred simultaneous quadruple whole-cell recordings from layer 5 pyramidal neurons in the rat visual cortex. Analysis of this dataset revealed several nonrandom features in synaptic connectivity. We confirmed previous reports that bidirectional connections are more common than expected in a random network. We found that several highly clustered three-neuron connectivity patterns are overrepresented, suggesting that connections tend to cluster together. We also analyzed synaptic connection strength as defined by the peak excitatory postsynaptic potential amplitude. We found that the distribution of synaptic connection strength differs significantly from the Poisson distribution and can be fitted by a lognormal distribution. Such a distribution has a heavier tail and implies that synaptic weight is concentrated among few synaptic connections. In addition, the strengths of synaptic connections sharing pre- or postsynaptic neurons are correlated, implying that strong connections are even more clustered than the weak ones. Therefore, the local cortical network structure can be viewed as a skeleton of stronger connections in a sea of weaker ones. Such a skeleton is likely to play an important role in network dynamics and should be investigated further.

Summary A key obstacle to understanding neural circuits in the cerebral cortex is that of unraveling the diversity of GABAergic interneurons. This diversity poses general questions for neural circuit analysis: how are these interneuron cell types generated and assembled into stereotyped local circuits and how do they differentially contribute to circuit operations that underlie cortical functions ranging from perception to cognition? Using genetic engineering in mice, we have generated and characterized ~20 Cre and inducible CreER knockin driver lines that reliably target major classes and lineages of GABAergic neurons. More select populations are captured by intersection of Cre and Flp drivers. Genetic targeting allows reliable identification, monitoring, and manipulation of cortical GABAergic neurons, thereby enabling a systematic and comprehensive analysis from cell fate specification, migration, and connectivity, to their functions in network dynamics and behavior. As such, this approach will accelerate the study of GABAergic circuits throughout the mammalian brain.

Synaptic plasticity provides the basis for most models of learning, memory and development in neural circuits. To generate realistic results, synapse-specific Hebbian forms of plasticity, such as long-term potentiation and depression, must be augmented by global processes that regulate overall levels of neuronal and network activity. Regulatory processes are often as important as the more intensively studied Hebbian processes in determining the consequences of synaptic plasticity for network function. Recent experimental results suggest several novel mechanisms for regulating levels of activity in conjunction with Hebbian synaptic modification. We review three of them-synaptic scaling, spike-timing dependent plasticity and synaptic redistribution-and discuss their functional implications.

Cortical long-term plasticity depends on firing rate, spike timing, and cooperativity among inputs, but how these factors interact during realistic patterns of activity is unknown. Here we monitored plasticity while systematically varying the rate, spike timing, and number of coincident afferents. These experiments demonstrate a novel form of cooperativity operating even when postsynaptic firing is evoked by current injection, and reveal a complex dependence of LTP and LTD on rate and timing. Based on these data, we constructed and tested three quantitative models of cortical plasticity. One of these models, in which spike-timing relationships causing LTP "win" out over those favoring LTD, closely fits the data and accurately predicts the build-up of plasticity during random firing. This provides a quantitative framework for predicting the impact of in vivo firing patterns on synaptic strength.

There is a consensus that NMDA receptors (NMDARs) detect coincident pre- and postsynaptic activity during induction of long-term potentiation (LTP), but their role in timing-dependent long-term depression (tLTD) is unclear. We examine tLTD in neocortical layer 5 (L5) pyramidal pairs and find that tLTD is expressed presynaptically, implying retrograde signaling. CB1 agonists produce depression that mimics and occludes tLTD. This agonist-induced LTD requires presynaptic activity and NMDAR activation, but not postsynaptic Ca(2+) influx. Further experiments demonstrate the existence of presynaptic NMDARs that underlie the presynaptic activity dependence. Finally, manipulating cannabinoid breakdown alters the temporal window for tLTD. In conclusion, tLTD requires simultaneous activation of presynaptic NMDA and CB1 receptors. This novel form of coincidence detection may explain the temporal window of tLTD and may also impart synapse specificity to cannabinoid retrograde signaling.

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts’ assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

The mechanisms underlying experience-dependent plasticity and refinement of central circuits are not yet fully understood. A non-Hebbian form of synaptic plasticity, which scales synaptic strengths up or down to stabilize firing rates, has recently been discovered in cultured neuronal networks. Here we demonstrate the existence of a similar mechanism in the intact rodent visual cortex. The frequency of miniature excitatory postsynaptic currents (mEPSCs) in principal neurons increased steeply between post-natal days 12 and 23. There was a concomitant decrease in mEPSC amplitude, which was prevented by rearing rats in complete darkness from 12 days of age. In addition, as little as two days of monocular deprivation scaled up mEPSC amplitude in a layer- and age-dependent manner. These data indicate that mEPSC amplitudes can be globally scaled up or down as a function of development and sensory experience, and suggest that synaptic scaling may be involved in the activity-dependent refinement of cortical connectivity.