How synaptic strength, short-term plasticity, and temporal factors contribute to neuronal spike output

To compute spiking responses, neurons integrate inputs from thousands of synapses whose strengths span an order of magnitude. Intriguingly, in mouse neocortex, the small minority of 'strong' synapses is found predominantly between similarly tuned cells, suggesting they are the synapses that determine a neuron's spike output. This raises the question of how other computational primitives, such as 'background' activity from the majority of synapses, which are 'weak', short-term plasticity, and temporal synchrony contribute to spiking. First, we combined extracellular stimulation and whole-cell recordings in mouse barrel cortex to map the distribution of excitatory postsynaptic potential (EPSP) amplitudes and paired-pulse ratios of excitatory synaptic connections converging onto individual layer 2/3 (L2/3) neurons. While generally net short-term plasticity was weak, connections with EPSPs > 2 mV displayed pronounced paired-pulse depression. EPSP amplitudes and paired-pulse ratios of connections converging onto the same neurons spanned the full range observed across L2/3 and there was no indication that strong synapses nor those with particular short-term plasticity properties were associated with particular cells, which critically constrains theoretical models of cortical filtering. To investigate how different computational primitives of synaptic information processing interact to shape spiking, we developed a computational model of a pyramidal neuron in the rodent L2/3 circuitry: firing rates and pairwise correlations of presynaptic inputs were constrained by in vivo observations, while synaptic strength and short-term plasticity were set based on our experimental data. Importantly, we found that the ability of strong inputs to evoke spiking critically depended on their high temporal synchrony and high firing rates observed in vivo and on synaptic background activity - and not primarily on synaptic strength, which in turn further enhanced information transfer. Depression of strong synapses was critical for maintaining a neuron's responsivity and prevented runaway excitation. Our results provide a holistic framework of how cortical neurons exploit complex synergies between temporal coding, synaptic properties, and noise in order to transform synaptic inputs into output firing.

Nonlinear transient amplification in recurrent neural networks with short-term plasticity

To rapidly process information, neural circuits have to amplify specific activity patterns transiently. How the brain performs this nonlinear operation remains elusive. Hebbian assemblies are one possibility whereby strong recurrent excitatory connections boost neuronal activity. However, such Hebbian amplification is often associated with dynamical slowing of network dynamics, non-transient attractor states, and pathological run-away activity. Feedback inhibition can alleviate these effects but typically linearizes responses and reduces amplification gain. Here we study nonlinear transient amplification (NTA), a plausible alternative mechanism that reconciles strong recurrent excitation with rapid amplification while avoiding the above issues. NTA has two distinct temporal phases. Initially, positive feedback excitation selectively amplifies inputs that exceed a critical threshold. Subsequently, short-term plasticity quenches the run-away dynamics into an inhibition-stabilized network state. By characterizing NTA in supralinear network models, we establish that the resulting onset transients are stimulus selective and well-suited for speedy information processing. Further, we find that excitatory-inhibitory co-tuning widens the parameter regime in which NTA is possible in the absence of persistent activity. In summary, NTA provides a parsimonious explanation for how excitatory-inhibitory co-tuning and short-term plasticity collaborate in recurrent networks to achieve transient amplification.

Memories in a network with excitatory and inhibitory plasticity are encoded in the spiking irregularity

Cell assemblies are thought to be the substrate of memory in the brain. Theoretical studies have previously shown that assemblies can be formed in networks with multiple types of plasticity. But how exactly they are formed and how they encode information is yet to be fully understood. One possibility is that memories are stored in silent assemblies. Here we used a computational model to study the formation of silent assemblies in a network of spiking neurons with excitatory and inhibitory plasticity. We found that even though the formed assemblies were silent in terms of mean firing rate, they had an increased coefficient of variation of inter-spike intervals. We also found that this spiking irregularity could be read out with support of short-term plasticity, and that it could contribute to the longevity of memories.

Short-Term Plasticity Regulates Both Divisive Normalization and Adaptive Responses in Drosophila Olfactory System

In Drosophila, olfactory information received by olfactory receptor neurons (ORNs) is first processed by an incoherent feed forward neural circuit in the antennal lobe (AL) that consists of ORNs (input), inhibitory local neurons (LNs), and projection neurons (PNs). This “early” olfactory information processing has two important characteristics. First, response of a PN to its cognate ORN is normalized by the overall activity of other ORNs, a phenomenon termed “divisive normalization.” Second, PNs respond strongly to the onset of ORN activities, but they adapt to prolonged or continuously varying inputs. Despite the importance of these characteristics for learning and memory, their underlying mechanisms are not fully understood. Here, we develop a circuit model for describing the ORN-LN-PN dynamics by including key neuron-neuron interactions such as short-term plasticity (STP) and presynaptic inhibition (PI). By fitting our model to experimental data quantitatively, we show that a strong STP balanced between short-term facilitation (STF) and short-term depression (STD) is responsible for the observed nonlinear divisive normalization in Drosophila. Our circuit model suggests that either STP or PI alone can lead to adaptive response. However, by comparing our model results with experimental data, we find that both STP and PI work together to achieve a strong and robust adaptive response. Our model not only helps reveal the mechanisms underlying two main characteristics of the early olfactory process, it can also be used to predict PN responses to arbitrary time-dependent signals and to infer microscopic properties of the circuit (such as the strengths of STF and STD) from the measured input-output relation. Our circuit model may be useful for understanding the role of STP in other sensory systems.

Modifying the m6A brain methylome by ALKBH5-mediated demethylation: a new contender for synaptic tagging

Synaptic plasticity processes, which underlie learning and memory formation, require RNA to be translated local to synapses. The synaptic tagging hypothesis has previously been proposed to explain how mRNAs are available at specific activated synapses. However how RNA is regulated, and which transcripts are silenced or processed as part of the tagging process is still unknown. Modification of RNA by N6-methyladenosine (m6A/m) influences the cellular fate of mRNA. Here, by advanced microscopy, we showed that m6A demethylation by the eraser protein ALKBH5 occurs at active synaptic ribosomes and at synapses during short term plasticity. We demonstrated that at activated glutamatergic post-synaptic sites, both the YTHDF1 and YTHDF3 reader and the ALKBH5 eraser proteins increase in co-localisation to m6A-modified RNAs; but only the readers showed high co-localisation to modified RNAs during late-stage plasticity. The YTHDF1 and YTHFDF3 readers also exhibited differential roles during synaptic maturation suggesting that temporal and subcellular abundance may determine specific function. m6A-sequencing of human parahippocampus brain tissue revealed distinct white and grey matter m6A methylome profiles indicating that cellular context is a fundamental factor dictating regulated pathways. However, in both neuronal and glial cell-rich tissue, m6A effector proteins are themselves modified and m6A epitranscriptional and posttranslational modification processes coregulate protein cascades. We hypothesise that the availability m6A effector protein machinery in conjunction with RNA modification, may be important in the formation of condensed synaptic nanodomain assemblies through liquid-liquid phase separation. Our findings support that m6A demethylation by ALKBH5 is an intrinsic component of the synaptic tagging hypothesis and a molecular switch which leads to alterations in the RNA methylome, synaptic dysfunction and potentially reversible disease states.

Short-term plasticity in the visual thalamus

While there is evidence that the visual cortex retains a potential for plasticity in adulthood, less is known about the subcortical stages of visual processing. Here we asked whether short-term ocular dominance plasticity affects the visual thalamus. We addressed this question in normally sighted adult humans, using ultra-high field (7T) magnetic resonance imaging combined with the paradigm of short-term monocular deprivation. With this approach, we previously demonstrated transient shifts of perceptual eye dominance and ocular dominance in visual cortex (Binda et al., 2018). Here we report evidence for short-term plasticity in the ventral division of the pulvinar (vPulv), where the deprived eye representation was enhanced over the non-deprived eye. This pulvinar plasticity effect was similar as previously seen in visual cortex and it was correlated with the ocular dominance shift measured behaviorally. In contrast, there was no short-term plasticity effect in Lateral Geniculate Nucleus (LGN), where results were reliably different from vPulv, despite their spatial proximity. We conclude that the visual thalamus retains potential for short-term plasticity in adulthood; the plasticity effect differs across thalamic subregions, possibly reflecting differences in their cortical connectivity.

TRPM7 is critical for short-term synaptic depression by regulating synaptic vesicle endocytosis

TRPM7 contributes to a variety of physiological and pathological processes in many tissues and cells. With a widespread distribution in the nervous system, TRPM7 is involved in animal behaviors and neuronal death induced by ischemia. However, the physiological role of TRPM7 in CNS neuron remains unclear. Here, we identify endocytic defects in neuroendocrine cells and neurons from TRPM7 knockout (KO) mice, indicating a role of TRPM7 in synaptic vesicle endocytosis. Our experiments further pinpoint the importance of TRPM7 as an ion channel in synaptic vesicle endocytosis. Ca2+ imaging detects a defect in presynaptic Ca2+ dynamics in TRPM7 KO neuron, suggesting an importance of Ca2+ influx via TRPM7 in synaptic vesicle endocytosis. Moreover, the short-term depression is enhanced in both excitatory and inhibitory synaptic transmission from TRPM7 KO mice. Taken together, our data suggests that Ca2+ influx via TRPM7 may be critical for short-term plasticity of synaptic strength by regulating synaptic vesicle endocytosis in neurons.

Temporal filters in response to presynaptic spike trains: Interplay of cellular, synaptic and short-term plasticity time scales

Temporal filters, the ability of postsynaptic neurons to preferentially select certain presynaptic input patterns, have been shown to be associated with the notion of information filtering and coding of sensory inputs. Their properties can be dynamically characterized as the transient responses to periodic presynaptic inputs. Short-term plasticity (STP) has been proposed to be an important player in the generation of temporal filters, but the response of postsynaptic neurons to presynaptic inputs depends on a collection of time scales in addition to STP's, which conspire to create temporal filters: the postsynaptic time scales generated by the cellular intrinsic currents and the presynaptic time scales captured by the ISI distribution patterns. The mechanisms by which these time scales and the processes giving rise to them interact to produce temporal filters in response to presynaptic input spike trains are not well understood. We carry out a systematic modeling and computational analysis to understand how the postsynaptic low-, high- and band-pass temporal filters are generated in response to periodic presynaptic spike trains in the presence STP, and how the dynamic properties of these filters depend on the interplay of a hierarchy of processes: arrival of the presynaptic spikes, the activation of STP and its effect on the synaptic connection efficacy, and the response of the postsynaptic cell. The time scales associated with each of these processes operate at the short-term, single-event level (they are activated at the arrival of each presynaptic spike) and collectively produce the long-term time scales that determine the shape and properties of the filters. We develop a series of mathematical tools to address these issues for a relatively simple model where depression and facilitation interact only at the level of the synaptic efficacy change as time progresses and we extend our results and tools to account for more complex models that involve interactions at the STP level and multiple STP time scales. We use these tools to understand the mechanisms of generation of temporal filters in the postsynaptic cells in terms of the properties and dynamics of the interacting building blocks.