Imaging synaptic plasticity

Neuronal Activity at Synapse Resolution: Reporters and Effectors for Synaptic Neuroscience

The development of methods for the activity-dependent tagging of neurons enabled a new way to tackle the problem of engram identification at the cellular level, giving rise to groundbreaking findings in the field of memory studies. However, the resolution of activity-dependent tagging remains limited to the whole-cell level. Notably, events taking place at the synapse level play a critical role in the establishment of new memories, and strong experimental evidence shows that learning and synaptic plasticity are tightly linked. Here, we provide a comprehensive review of the currently available techniques that enable to identify and track the neuronal activity with synaptic spatial resolution. We also present recent technologies that allow to selectively interfere with specific subsets of synapses. Lastly, we discuss how these technologies can be applied to the study of learning and memory.

A two-compartment model of synaptic computation and plasticity

The synapse is typically viewed as a single compartment, which acts as a linear gain controller on incoming input. Traditional plasticity rules enable this gain control to be dynamically optimized by Hebbian activity. Whilst this view nicely captures postsynaptic function, it neglects the non-linear dynamics of presynaptic function. Here we present a two-compartment model of the synapse in which the presynaptic terminal first acts to filter presynaptic input before the postsynaptic terminal, acting as a gain controller, amplifies or depresses transmission. We argue that both compartments are equipped with distinct plasticity rules to enable them to optimally adapt synaptic transmission to the statistics of pre- and postsynaptic activity. Specifically, we focus on how presynaptic plasticity enables presynaptic filtering to be optimally tuned to only transmit information relevant for postsynaptic firing. We end by discussing the advantages of having a presynaptic filter and propose future work to explore presynaptic function and plasticity in vivo.

Glutamate is required for depression but not potentiation of long-term presynaptic function

Hebbian plasticity is thought to require glutamate signalling. We show this is not the case for hippocampal presynaptic long-term potentiation (LTP_pre), which is expressed as an increase in transmitter release probability (P_r). We find that LTP_pre can be induced by pairing pre- and postsynaptic spiking in the absence of glutamate signalling. LTP_pre induction involves a non-canonical mechanism of retrograde nitric oxide signalling, which is triggered by Ca²⁺ influx from L-type voltage-gated Ca²⁺ channels, not postsynaptic NMDA receptors (NMDARs), and does not require glutamate release. When glutamate release occurs, it decreases P_r by activating presynaptic NMDARs, and promotes presynaptic long-term depression. Net changes in P_r, therefore, depend on two opposing factors: (1) Hebbian activity, which increases P_r, and (2) glutamate release, which decreases P_r. Accordingly, release failures during Hebbian activity promote LTP_pre induction. Our findings reveal a novel framework of presynaptic plasticity that radically differs from traditional models of postsynaptic plasticity.

Neurons communicate with one another at junctions called synapses. One neuron at the synapse releases a chemical substance called a neurotransmitter, which binds to and activates the other neuron. The release of neurotransmitter thus enables the electrical activity of one cell to influence the electrical activity of another. The efficiency of this communication can change over time, as is thought to occur during learning. If the neurons on both sides of a synapse are repeatedly active at the same time, the ability of the neurons to transmit electrical signals to each other increases.

One way that communication between neurons can become more efficient is if the first neuron becomes more likely to release neurotransmitter. Most synapses in the brain release a neurotransmitter called glutamate, and most types of learning involve changes in the efficiency of communication at glutamatergic synapses. But glutamate release is unreliable. Active glutamatergic neurons fail to release glutamate about 80% of the time. If glutamate has a key role in learning, how does the brain learn efficiently when glutamate release is so unlikely?

To find out, Padamsey et al. studied glutamatergic synapses in slices of tissue from mouse and rat brains. When both neurons at a synapse were repeatedly active at the same time, the first neuron would sometimes become more likely to release glutamate. But this only happened at synapses in which the first neuron usually failed to release glutamate in the first place. This suggests that communication failures help to drive change at synapses. When two neurons that are often active at the same time do not communicate efficiently, this failure triggers molecular changes that make future communication more reliable.

Previous results have shown that synapses can change when glutamate release occurs. The current results show that they can also change when it does not. This means that the brain can continue to learn despite frequent communication failures between neurons. Many neurological disorders, including Alzheimer’s disease, show altered glutamate signalling at synapses. Padamsey et al. hope that a better understanding of this process will lead to new therapies for these disorders.

Quadruplex Integrated DNA (QuID) Nanosensors for Monitoring Dopamine

Dopamine is widely innervated throughout the brain and critical for many cognitive and motor functions. Imbalances or loss in dopamine transmission underlie various psychiatric disorders and degenerative diseases. Research involving cellular studies and disease states would benefit from a tool for measuring dopamine transmission. Here we show a Quadruplex Integrated DNA (QuID) nanosensor platform for selective and dynamic detection of dopamine. This nanosensor exploits DNA technology and enzyme recognition systems to optically image dopamine levels. The DNA quadruplex architecture is designed to be compatible in physically constrained environments (110 nm) with high flexibility, homogeneity, and a lower detection limit of 110 µM.

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

Neuronal activity-dependent regulation of MicroRNAs

MicroRNAs are non-coding short (~23 nucleotides) RNAs that mediate post-transcriptional regulation through sequence-specific gene silencing. The role of miRNAs in neuronal development, synapse formation and synaptic plasticity has been highlighted. However, the role of neuronal activity on miRNA regulation has been less focused. Neuronal activity-dependent regulation of miRNA may fine-tune gene expression in response to synaptic plasticity and memory formation. Here, we provide an overview of miRNA regulation by neuronal activity including high-throughput screening studies. We also discuss the possible molecular mechanisms of activity-dependent induction and turnover of miRNAs.

Upregulation of excitatory neurons and downregulation of inhibitory neurons in barrel cortex are associated with loss of whisker inputs

Loss of a sensory input causes the hypersensitivity in other modalities. In addition to cross-modal plasticity, the sensory cortices without receiving inputs undergo the plastic changes. It is not clear how the different types of neurons and synapses in the sensory cortex coordinately change after input deficits in order to prevent loss of their functions and to be used for other modalities. We studied this subject in the barrel cortices from whiskers-trimmed mice vs. controls. After whisker trimming for a week, the intrinsic properties of pyramidal neurons and the transmission of excitatory synapses were upregulated in the barrel cortex, but inhibitory neurons and GABAergic synapses were downregulated. The morphological analyses indicated that the number of processes and spines in pyramidal neurons increased, whereas the processes of GABAergic neurons decreased in the barrel cortex. The upregulation of excitatory neurons and the downregulation of inhibitory neurons boost the activity of network neurons in the barrel cortex to be high levels, which prevent the loss of their functions and enhances their sensitivity to sensory inputs. These changes may prepare for attracting the innervations from sensory cortices and/or peripheral nerves for other modalities during cross-modal plasticity.

Upregulation of transmitter release probability improves a conversion of synaptic analogue signals into neuronal digital spikes

Action potentials at the neurons and graded signals at the synapses are primary codes in the brain. In terms of their functional interaction, the studies were focused on the influence of presynaptic spike patterns on synaptic activities. How the synapse dynamics quantitatively regulates the encoding of postsynaptic digital spikes remains unclear. We investigated this question at unitary glutamatergic synapses on cortical GABAergic neurons, especially the quantitative influences of release probability on synapse dynamics and neuronal encoding. Glutamate release probability and synaptic strength are proportionally upregulated by presynaptic sequential spikes. The upregulation of release probability and the efficiency of probability-driven synaptic facilitation are strengthened by elevating presynaptic spike frequency and Ca²⁺. The upregulation of release probability improves spike capacity and timing precision at postsynaptic neuron. These results suggest that the upregulation of presynaptic glutamate release facilitates a conversion of synaptic analogue signals into digital spikes in postsynaptic neurons, i.e., a functional compatibility between presynaptic and postsynaptic partners.