Comparing mouse and human brains.

Inhibitory circuit motifs in the mouse brain and the human brain are strikingly similar.

The developmental profile of visual cortex astrocytes.

We investigated how astrocytes in layer 5 mouse visual cortex mature over postnatal days (P) 3-50. Across this age range, resting membrane potential increased, input resistance decreased, and membrane responses became more passive with age. Two-photon (2p) and confocal imaging of dye-loaded cells revealed that gap-junction coupling increased starting ∼P7. Morphological reconstructions revealed increased branch density but shorter branches after P20, suggesting that astrocyte branches may get pruned as tiling is established. Finally, we visualized spontaneous Ca2+ transients with 2p microscopy and found that Ca2+ events decorrelated, became more frequent and briefer with age. As astrocytes mature, spontaneous Ca2+ activity thus changes from relatively cell-wide, synchronous waves to local transients. Several astrocyte properties were stably mature from ∼P15, coinciding with eye opening, although morphology continued to develop. Our findings provide a descriptive foundation of astrocyte maturation, useful for the study of astrocytic impact on visual cortex critical period plasticity.

Pre- and postsynaptically expressed spike-timing-dependent plasticity contribute differentially to neuronal learning.

A plethora of experimental studies have shown that long-term synaptic plasticity can be expressed pre- or postsynaptically depending on a range of factors such as developmental stage, synapse type, and activity patterns. The functional consequences of this diversity are not clear, although it is understood that whereas postsynaptic expression of plasticity predominantly affects synaptic response amplitude, presynaptic expression alters both synaptic response amplitude and short-term dynamics. In most models of neuronal learning, long-term synaptic plasticity is implemented as changes in connective weights. The consideration of long-term plasticity as a fixed change in amplitude corresponds more closely to post- than to presynaptic expression, which means theoretical outcomes based on this choice of implementation may have a postsynaptic bias. To explore the functional implications of the diversity of expression of long-term synaptic plasticity, we adapted a model of long-term plasticity, more specifically spike-timing-dependent plasticity (STDP), such that it was expressed either independently pre- or postsynaptically, or in a mixture of both ways. We compared pair-based standard STDP models and a biologically tuned triplet STDP model, and investigated the outcomes in a minimal setting, using two different learning schemes: in the first, inputs were triggered at different latencies, and in the second a subset of inputs were temporally correlated. We found that presynaptic changes adjusted the speed of learning, while postsynaptic expression was more efficient at regulating spike timing and frequency. When combining both expression loci, postsynaptic changes amplified the response range, while presynaptic plasticity allowed control over postsynaptic firing rates, potentially providing a form of activity homeostasis. Our findings highlight how the seemingly innocuous choice of implementing synaptic plasticity by single weight modification may unwittingly introduce a postsynaptic bias in modelling outcomes. We conclude that pre- and postsynaptically expressed plasticity are not interchangeable, but enable complimentary functions.

Novel Optogenetic Approaches in Epilepsy Research.

Epilepsy is a major neurological disorder characterized by repeated seizures afflicting 1% of the global population. The emergence of seizures is associated with several comorbidities and severely decreases the quality of life of patients. Unfortunately, around 30% of patients do not respond to first-line treatment using anti-seizure drugs (ASDs). Furthermore, it is still unclear how seizures arise in the healthy brain. Therefore, it is critical to have well developed models where a causal understanding of epilepsy can be investigated. While the development of seizures has been studied in several animal models, using chemical or electrical induction, deciphering the results of such studies has been difficult due to the uncertainty of the cell population being targeted as well as potential confounds such as brain damage from the procedure itself. Here we describe novel approaches using combinations of optical and genetic methods for studying epileptogenesis. These approaches can circumvent some shortcomings associated with the classical animal models and may thus increase the likelihood of developing new treatment options.

CosMIC: A Consistent Metric for Spike Inference from Calcium Imaging.

In recent years, the development of algorithms to detect neuronal spiking activity from two-photon calcium imaging data has received much attention, yet few researchers have examined the metrics used to assess the similarity of detected spike trains with the ground truth. We highlight the limitations of the two most commonly used metrics, the spike train correlation and success rate, and propose an alternative, which we refer to as CosMIC. Rather than operating on the true and estimated spike trains directly, the proposed metric assesses the similarity of the pulse trains obtained from convolution of the spike trains with a smoothing pulse. The pulse width, which is derived from the statistics of the imaging data, reflects the temporal tolerance of the metric. The final metric score is the size of the commonalities of the pulse trains as a fraction of their average size. Viewed through the lens of set theory, CosMIC resembles a continuous Sørensen-Dice coefficient-an index commonly used to assess the similarity of discrete, presence/absence data. We demonstrate the ability of the proposed metric to discriminate the precision and recall of spike train estimates. Unlike the spike train correlation, which appears to reward overestimation, the proposed metric score is maximized when the correct number of spikes have been detected. Furthermore, we show that CosMIC is more sensitive to the temporal precision of estimates than the success rate.

Differential Regulation of Evoked and Spontaneous Release by Presynaptic NMDA Receptors.

Presynaptic NMDA receptors (preNMDARs) control synaptic release, but it is not well understood how. Rab3-interacting molecules (RIMs) provide scaffolding at presynaptic active zones and are involved in vesicle priming. Moreover, c-Jun N-terminal kinase (JNK) has been implicated in regulation of spontaneous release. We demonstrate that, at connected layer 5 pyramidal cell pairs of developing mouse visual cortex, Mg2+-sensitive preNMDAR signaling upregulates replenishment of the readily releasable vesicle pool during high-frequency firing. In conditional RIM1αß deletion mice, preNMDAR upregulation of vesicle replenishment was abolished, yet preNMDAR control of spontaneous release was unaffected. Conversely, JNK2 blockade prevented Mg2+-insensitive preNMDAR signaling from regulating spontaneous release, but preNMDAR control of evoked release remained intact. We thus discovered that preNMDARs signal differentially to control evoked and spontaneous release by independent and non-overlapping mechanisms. Our findings suggest that preNMDARs may sometimes signal metabotropically and support the emerging principle that evoked and spontaneous release are distinct processes. VIDEO ABSTRACT.

A history of spike-timing-dependent plasticity.

How learning and memory is achieved in the brain is a central question in neuroscience. Key to today's research into information storage in the brain is the concept of synaptic plasticity, a notion that has been heavily influenced by Hebb's (1949) postulate. Hebb conjectured that repeatedly and persistently co-active cells should increase connective strength among populations of interconnected neurons as a means of storing a memory trace, also known as an engram. Hebb certainly was not the first to make such a conjecture, as we show in this history. Nevertheless, literally thousands of studies into the classical frequency-dependent paradigm of cellular learning rules were directly inspired by the Hebbian postulate. But in more recent years, a novel concept in cellular learning has emerged, where temporal order instead of frequency is emphasized. This new learning paradigm - known as spike-timing-dependent plasticity (STDP) - has rapidly gained tremendous interest, perhaps because of its combination of elegant simplicity, biological plausibility, and computational power. But what are the roots of today's STDP concept? Here, we discuss several centuries of diverse thinking, beginning with philosophers such as Aristotle, Locke, and Ribot, traversing, e.g., Lugaro's plasticità and Rosenblatt's perceptron, and culminating with the discovery of STDP. We highlight interactions between theoretical and experimental fields, showing how discoveries sometimes occurred in parallel, seemingly without much knowledge of the other field, and sometimes via concrete back-and-forth communication. We point out where the future directions may lie, which includes interneuron STDP, the functional impact of STDP, its mechanisms and its neuromodulatory regulation, and the linking of STDP to the developmental formation and continuous plasticity of neuronal networks.

Multiple forms of long-term plasticity at unitary neocortical layer 5 synapses.

Long-term potentiation and depression (LTP and LTD) are cellular plasticity phenomena expressed at a variety of central synapses, and are thought to contribute to learning and developmental changes in circuitry. Recurrent neocortical layer-5 synapses are thought to express a presynaptic form of LTP that influences the short-term plasticity of the synapse. Here we show that changes in synaptic strength elicited by pairing high frequency pre- and postsynaptic firing at this synapse result from a mixture of presynaptic and postsynaptic forms of plasticity, as assessed by the analysis of changes in coefficient of variation, short-term plasticity, and NMDA:AMPA current ratios. Pharmacological dissection of this plasticity revealed that block of presynaptic LTD with an endocannabinoid inhibitor enhanced LTP, while the apparently presynaptic component of LTP could be prevented by induction in the presence of blockers of nitric oxide. These data suggest that correlated high-frequency firing at layer-5 synapses simultaneously induces a mixture of presynaptic LTD, presynaptic LTP, and postsynaptic LTP.

Optimal information storage in noisy synapses under resource constraints.

Experimental investigations have revealed that synapses possess interesting and, in some cases, unexpected properties. We propose a theoretical framework that accounts for three of these properties: typical central synapses are noisy, the distribution of synaptic weights among central synapses is wide, and synaptic connectivity between neurons is sparse. We also comment on the possibility that synaptic weights may vary in discrete steps. Our approach is based on maximizing information storage capacity of neural tissue under resource constraints. Based on previous experimental and theoretical work, we use volume as a limited resource and utilize the empirical relationship between volume and synaptic weight. Solutions of our constrained optimization problems are not only consistent with existing experimental measurements but also make nontrivial predictions.

A cooperative switch determines the sign of synaptic plasticity in distal dendrites of neocortical pyramidal neurons.

Pyramidal neurons in the cerebral cortex span multiple cortical layers. How the excitable properties of pyramidal neuron dendrites allow these neurons to both integrate activity and store associations between different layers is not well understood, but is thought to rely in part on dendritic backpropagation of action potentials. Here we demonstrate that the sign of synaptic plasticity in neocortical pyramidal neurons is regulated by the spread of the backpropagating action potential to the synapse. This creates a progressive gradient between LTP and LTD as the distance of the synaptic contacts from the soma increases. At distal synapses, cooperative synaptic input or dendritic depolarization can switch plasticity between LTD and LTP by boosting backpropagation of action potentials. This activity-dependent switch provides a mechanism for associative learning across different neocortical layers that process distinct types of information.

Novel presynaptic mechanisms for coincidence detection in synaptic plasticity.

Long-term plasticity typically relies on postsynaptic NMDA receptors to detect the coincidence of pre- and postsynaptic activity. Recent studies, however, have revealed forms of plasticity that depend on coincidence detection by presynaptic NMDA receptors. In the amygdala, cortical afferent associative presynaptic long-term potentiation (LTP) requires activation of presynaptic NMDA receptors by simultaneous thalamic and cortical afferents. Surprisingly, both types of afferent can also undergo postsynaptically induced NMDA-receptor-dependent LTP. In the neocortex, spike-timing-dependent long-term depression (LTD) requires simultaneous activation of presynaptic NMDA autoreceptors and retrograde signalling by endocannabinoids. In cerebellar LTD, presynaptic NMDA receptor activation suggests that similar presynaptic mechanisms may exist. Recent studies also indicate the existence of presynaptic coincidence detection that is independent of NMDA receptors, suggesting that such mechanisms have a widespread role in plasticity.

Highly nonrandom features of synaptic connectivity in local cortical circuits.

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.

Endocannabinoid-dependent neocortical layer-5 LTD in the absence of postsynaptic spiking.

Long-term depression (LTD) was induced in neocortical layer 5 pyramidal connections by pairing presynaptic firing with subthreshold postsynaptic depolarization (dLTD) or via a spike-timing protocol (tLTD). Like tLTD, dLTD reduced short-term depression and increased the coefficient of variation consistent with a presynaptic site of expression. Also like tLTD, dLTD was blocked by CB1 cannibinoid receptor blockade and required activation of presumably presynaptic NR2B-containing N-methyl-D-aspartate receptors. The two forms of LTD had identical magnitudes and time courses and occluded one another, and neither depended on frequency. Finally, dLTD shares with tLTD the asymmetric temporal window of induction. In conclusion, the types of LTD induced by these two protocols are indistinguishable, suggesting that the mechanism that underlies tLTD paradoxically does not require postsynaptic spiking: The subthreshold postsynaptic depolarizations of dLTD appear to fully substitute for postsynaptic spiking.

A proportional but slower NMDA potentiation follows AMPA potentiation in LTP.

Most excitatory glutamatergic synapses contain both AMPA and NMDA receptors, but whether these receptors are regulated together or independently during synaptic plasticity has been controversial. Although long-term potentiation (LTP) is thought to selectively enhance AMPA currents and alter the NMDA-to-AMPA ratio, this ratio is well conserved across synapses onto the same neuron. This suggests that the NMDA-to-AMPA ratio is only transiently perturbed by LTP. To test this, we induced LTP at rat neocortical synapses and recorded mixed AMPA-NMDA currents. We observed rapid LTP of AMPA currents, as well as delayed potentiation of NMDA currents that required previous AMPA potentiation. The delayed potentiation of NMDA currents restored the original NMDA-to-AMPA ratio within 2 h of LTP induction. These data suggest that recruitment of AMPA receptors to synapses eventually induces a proportional increase in NMDA current. This may ensure that LTP does not alter the relative contributions of these two receptors to synaptic transmission and information processing.

Neocortical LTD via coincident activation of presynaptic NMDA and cannabinoid receptors.

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.

Spike timing, calcium signals and synaptic plasticity.

Plasticity at central synapses depends critically on the timing of presynaptic and postsynaptic action potentials. Key initial steps in synaptic plasticity involve the back-propagation of action potentials into the dendritic tree and calcium influx that depends nonlinearly on the action potential and synaptic input. These initial steps are now better understood. In addition, recent studies of processes as diverse as gene expression and channel inactivation suggest that responses to calcium transients depend not only their amplitude, but on their time course and on the location of their origin.

Rate and timing in cortical synaptic plasticity.

Debate has raged over the past few years as to whether cortical neurons transmit information primarily in their average firing rates or in the precise timing of their spikes. Here, we address the related question of which features of spike trains control plasticity at cortical synapses. Using paired recording in slices we have developed a quantitative and predictive description of the joint dependence of cortical plasticity on the rate and relative timing of pre- and postsynaptic firing. The results hold important implications for which parts of the neural code are most readily stored for later retrieval.