Presynaptic adenosine receptor-mediated regulation of diverse thalamocortical short-term plasticity in the mouse whisker pathway

Short-term synaptic plasticity (STP) sets the sensitivity of a synapse to incoming activity and determines the temporal patterns that it best transmits. In “driver” thalamocortical (TC) synaptic populations, STP is dominated by depression during stimulation from rest. However, during ongoing stimulation, lemniscal TC connections onto layer 4 neurons in mouse barrel cortex express variable STP. Each synapse responds to input trains with a distinct pattern of depression or facilitation around its mean steady-state response. As a result, in common with other synaptic populations, lemniscal TC synapses express diverse rather than uniform dynamics, allowing for a rich representation of temporally varying stimuli. Here, we show that this STP diversity is regulated presynaptically. Presynaptic adenosine receptors of the A1R type, but not kainate receptors (KARs), modulate STP behavior. Blocking the receptors does not eliminate diversity, indicating that diversity is related to heterogeneous expression of multiple mechanisms in the pathway from presynaptic calcium influx to neurotransmitter release

Double Inverse Stochastic Resonance with Dynamic Synapses

We investigate the behavior of a model neuron that receives a biophysically-realistic noisy post-synaptic current based on uncorrelated spiking activity from a large number of afferents. We show that, with static synapses, such noise can give rise to inverse stochastic resonance (ISR) as a function of the presynaptic firing rate. We compare this to the case with dynamic synapses that feature short-term synaptic plasticity, and show that the interval of presynaptic firing rate over which ISR exists can be extended or diminished. We consider both short-term depression and facilitation. Interestingly, we find that a double inverse stochastic resonance (DISR), with two distinct wells centered at different presynaptic firing rates, can appear.Comment: 12 pages, 7 figure

Phase changes in neuronal postsynaptic spiking due to short term plasticity

In the brain, the postsynaptic response of a neuron to time-varying inputs is determined by the interaction of presynaptic spike times with the short-term dynamics of each synapse. For a neuron driven by stochastic synapses, synaptic depression results in a quite different postsynaptic response to a large population input depending on how correlated in time the spikes across individual synapses are. Here we show using both simulations and mathematical analysis that not only the rate but the phase of the postsynaptic response to a rhythmic population input varies as a function of synaptic dynamics and synaptic configuration. Resultant phase leads may compensate for transmission delays and be predictive of rhythmic changes. This could be particularly important for sensory processing and motor rhythm generation in the nervous system. © 2017 McDonnell, Graham

Ultrafast glutamate sensors resolve high-frequency release at Schaffer collateral synapses

Glutamatergic synapses display a rich repertoire of plasticity mechanisms on many different time scales, involving dynamic changes in the efficacy of transmitter release as well as changes in the number and function of postsynaptic glutamate receptors. The genetically encoded glutamate sensor iGluSnFR enables visualization of glutamate release from presynaptic terminals at frequencies up to ∼10 Hz. However, to resolve glutamate dynamics during high-frequency bursts, faster indicators are required. Here, we report the development of fast (iGluf) and ultrafast (iGluu) variants with comparable brightness but increased Kd for glutamate (137 μM and 600 μM, respectively). Compared with iGluSnFR, iGluu has a sixfold faster dissociation rate in vitro and fivefold faster kinetics in synapses. Fitting a three-state model to kinetic data, we identify the large conformational change after glutamate binding as the rate-limiting step. In rat hippocampal slice culture stimulated at 100 Hz, we find that iGluu is sufficiently fast to resolve individual glutamate release events, revealing that glutamate is rapidly cleared from the synaptic cleft. Depression of iGluu responses during 100-Hz trains correlates with depression of postsynaptic EPSPs, indicating that depression during high-frequency stimulation is purely presynaptic in origin. At individual boutons, the recovery from depression could be predicted from the amount of glutamate released on the second pulse (paired pulse facilitation/depression), demonstrating differential frequency-dependent filtering of spike trains at Schaffer collateral boutons

Slowness: An Objective for Spike-Timing-Dependent Plasticity?

Slow Feature Analysis (SFA) is an efficient algorithm for learning input-output functions that extract the most slowly varying features from a quickly varying signal. It has been successfully applied to the unsupervised learning of translation-, rotation-, and other invariances in a model of the visual system, to the learning of complex cell receptive fields, and, combined with a sparseness objective, to the self-organized formation of place cells in a model of the hippocampus. In order to arrive at a biologically more plausible implementation of this learning rule, we consider analytically how SFA could be realized in simple linear continuous and spiking model neurons. It turns out that for the continuous model neuron SFA can be implemented by means of a modified version of standard Hebbian learning. In this framework we provide a connection to the trace learning rule for invariance learning. We then show that for Poisson neurons spike-timing-dependent plasticity (STDP) with a specific learning window can learn the same weight distribution as SFA. Surprisingly, we find that the appropriate learning rule reproduces the typical STDP learning window. The shape as well as the timescale are in good agreement with what has been measured experimentally. This offers a completely novel interpretation for the functional role of spike-timing-dependent plasticity in physiological neurons

Correlation entropy of synaptic input-output dynamics

The responses of synapses in the neocortex show highly stochastic and nonlinear behavior. The microscopic dynamics underlying this behavior, and its computational consequences during natural patterns of synaptic input, are not explained by conventional macroscopic models of deterministic ensemble mean dynamics. Here, we introduce the correlation entropy of the synaptic input-output map as a measure of synaptic reliability which explicitly includes the microscopic dynamics. Applying this to experimental data, we find that cortical synapses show a low-dimensional chaos driven by the natural input pattern.Comment: 7 pages, 6 Figures (7 figure files

Postsynaptic Mechanisms Are Essential for Forskolin-Induced Potentiation of Synaptic Transmission

It has been demonstrated that stimulation of protein kinase A (PKA) results in enhanced synaptic transmission in the hippocampus and other brain areas. To investigate mechanisms of the PKA-mediated potentiation of synaptic transmission, we used rat hippocampal embryonic cultures. In low-density cultures, paired recordings under the perforated patch demonstrated that 15-min forskolin treatment produced long-lasting potentiation of evoked excitatory postsynaptic currents (eEPSCs) mediated by the cAMP/PKA pathway. eEPSC amplitudes increased to 240 ± 10% of baseline after 15 min of forskolin treatment (early). After forskolin washout, eEPSCs declined to a potentiated level. Potentiation was sustained for ≥85 min after forskolin washout and, 60 min after forskolin washout, constituted 152 ± 7% of baseline (late potentiation). Disruption of presynaptic processes with the whole cell configuration and internal solution containing PKA inhibitor peptide did not affect forskolin-induced potentiation. Disruption of postsynaptic processes, in contrast, impaired early potentiation and abolished late potentiation. Study of mEPSCs confirmed the contribution of postsynaptic mechanisms. Forskolin-induced enhancement of mEPSC frequency observed under the perforated patch was attenuated by the whole cell configuration. Forskolin also induced an increase of mEPSC amplitudes in the perforated patch, but not in the whole cell, experiments. Potentiation of eEPSCs was not activity dependent, persisting in the absence of stimulation. NMDA receptor blockade did not abolish forskolin-induced potentiation. In summary, we demonstrate that forskolin-induced potentiation of eEPSCs was mediated by postsynaptic mechanisms, presumably by upregulation of AMPA receptors by phosphorylation