The Stimulatory Effects of Intracellular α-Synuclein on Synaptic Transmission Are Attenuated by 2-Octahydroisoquinolin-2(1H)-ylethanamine

α-Synuclein (αSyn) species can be detected in synaptic boutons, where they play a crucial role in the pathogenesis of Parkinson’s Disease (PD). However, the effects of intracellular αSyn species on synaptic transmission have not been thoroughly studied. Here, using patch-clamp recordings in hippocampal neurons, we report that αSyn oligomers (αSynO), intracellularly delivered through the patch electrode, produced a fast and potent effect on synaptic transmission, causing a substantial increase in the frequency, amplitude and transferred charge of spontaneous synaptic currents. We also found an increase in the frequency of miniature synaptic currents, suggesting an effect located at the presynaptic site of the synapsis. Furthermore, our in silico approximation using docking analysis and molecular dynamics simulations showed an interaction between a previously described small anti-amyloid beta (Aβ) molecule, termed M30 (2-octahydroisoquinolin-2(1H)-ylethanamine), with a central hydrophobic region of αSyn. In line with this finding, our empirical data aimed to obtain oligomerization states with thioflavin T (ThT) and Western blot (WB) indicated that M30 interfered with αSyn aggregation and decreased the formation of higher-molecular-weight species. Furthermore, the effect of αSynO on synaptic physiology was also antagonized by M30, resulting in a decrease in the frequency, amplitude, and charge transferred of synaptic currents. Overall, the present results show an excitatory effect of intracellular αSyn low molecular-weight species, not previously described, that are able to affect synaptic transmission, and the potential of a small neuroactive molecule to interfere with the aggregation process and the synaptic effect of αSyn, suggesting that M30 could be a potential therapeutic strategy for synucleinopathies.

Downstream projection of Barrington's nucleus to the spinal cord in mice

Barrington's nucleus (Bar) which controls micturition behavior through downstream projections to the spinal cord contains two types of projection neurons BarCRH and BarESR1 that have different functions and target different spinal circuitry. Both types of neurons project to the L6-S1 spinal intermediolateral (IML) nucleus while BarESR1 neurons also project to the dorsal commissural nucleus (DCN). To obtain more information about the spinal circuits targeted by Bar, we used patch-clamp recording in spinal slices from adult mice in combination with optogenetic stimulation of Bar terminals. Recording of opto-evoked excitatory post synaptic currents (oEPSCs) in DiI-labeled lumbosacral preganglionic neurons (LS-PGN) revealed that both Bar neuronal populations make strong glutamatergic monosynaptic connections with LS-PGN, while BarESR1 neurons also elicited smaller amplitude glutamatergic polysynaptic oEPSCs or polysynaptic inhibitory post synaptic currents (oIPSCs) in some LS-PGN. Optical stimulation of BarCRH and BarESR1 terminals also elicited monosynaptic oEPSCs and polysynaptic oIPSCs in sacral DCN neurons, some of which must include interneurons projecting either to the IML or ventral horn. Application of capsaicin increased opto-evoked firing during repetitive stimulation of Bar terminals through the modulation of spontaneous post synaptic currents in LS-PGN. In conclusion, our experiments have provided insights into the synaptic mechanisms underlying the integration of inputs from Bar to autonomic circuitry in the lumbosacral spinal cord that may control micturition.

Analysis and extension of exact mean-field theory with dynamic synaptic currents

Neural mass models such as the Jansen-Rit system provide a practical framework for representing and interpreting electrophysiological activity (1-6) in both local and global brain models (7). However, they are only partly derived from first principles. While the post-synaptic potential dynamics in NMM are inferred from data and can be grounded on diffusion physics (8-10), Freeman's "wave to pulse" sigmoid function (11-13) is used to transduce mean population membrane potential into firing rate rests on a weaker theoretical standing. On the other hand, Montbrio et al (14, 15) derive an exact mean-field theory from a quadratic integrate and fire neuron model under some simplifying assumptions (MPR), connecting microscale neural mechanisms and meso/macroscopic phenomena. The MPR model can be seen to replace Freeman's sigmoid function with a pair of differential equations for the mean membrane potential and firing rate variables, providing a mechanistic interpretation of NMM semi-empirical sigmoid parameters. In doing so, it sheds light on the mechanisms behind enhanced network response to weak but uniform perturbations: in the exact mean-field theory, intrinsic population connectivity modulates the steady-state firing rate transfer function in a monotonic manner, with increasing self-connectivity leading to higher firing rates. This provides a plausible mechanism for the enhanced response of densely connected networks to weak, uniform inputs such as the electric fields produced by non-invasive brain stimulation. Finally, we complete the MPR model by adding the equations for delayed post-synaptic currents, bringing together the MPR and NMM formalisms into a unified exact mean-field theory (NMM2) displaying rich dynamical features. As an example, we analyze the dynamics of a single population model, and a model of two coupled populations with a simple excitation-inhibition (E-I) architecture, showing it displays rich dynamics with limit cycles, period doubling, bursting behavior, and enhanced sensitivity to external inputs.

Computation of the electroencephalogram (EEG) from network models of point neurons

The electroencephalogram (EEG) is a major tool for non-invasively studying brain function and dysfunction. Comparing experimentally recorded EEGs with neural network models is important to better interpret EEGs in terms of neural mechanisms. Most current neural network models use networks of simple point neurons. They capture important properties of cortical dynamics, and are numerically or analytically tractable. However, point neurons cannot generate an EEG, as EEG generation requires spatially separated transmembrane currents. Here, we explored how to compute an accurate approximation of a rodent’s EEG with quantities defined in point-neuron network models. We constructed different approximations (or proxies) of the EEG signal that can be computed from networks of leaky integrate-and-fire (LIF) point neurons, such as firing rates, membrane potentials, and combinations of synaptic currents. We then evaluated how well each proxy reconstructed a ground-truth EEG obtained when the synaptic currents of the LIF model network were fed into a three-dimensional network model of multicompartmental neurons with realistic morphologies. Proxies based on linear combinations of AMPA and GABA currents performed better than proxies based on firing rates or membrane potentials. A new class of proxies, based on an optimized linear combination of time-shifted AMPA and GABA currents, provided the most accurate estimate of the EEG over a wide range of network states. The new linear proxies explained 85–95% of the variance of the ground-truth EEG for a wide range of network configurations including different cell morphologies, distributions of presynaptic inputs, positions of the recording electrode, and spatial extensions of the network. Non-linear EEG proxies using a convolutional neural network (CNN) on synaptic currents increased proxy performance by a further 2–8%. Our proxies can be used to easily calculate a biologically realistic EEG signal directly from point-neuron simulations thus facilitating a quantitative comparison between computational models and experimental EEG recordings.

Effects of Ih and TASK-like shunting current on dendritic impedance in layer 5 pyramidal-tract neurons

We simulated chirp current stimulation in the apical dendrites of 5 biophysically detailed multicompartment models of neocortical pyramidal tract neurons and found that a combination of HCN channels and TASK-like channels produced the best fit to experimental measurements of dendritic impedance. We then explored how HCN and TASK-like channels can shape the dendritic impedance as well as the voltage response to synaptic currents.

Periodic unitary synaptic currents in the mouse globus pallidus during spontaneous firing in slices

Neurons in the external globus pallidus (GPe) are autonomous pacemakers, but their spontaneous firing is continually perturbed by synaptic input. Because GPe neurons fire rhythmically in slices, spontaneous inhibitory synaptic currents (IPSCs) should be evident there. We identified periodic series of IPSCs in slices, each corresponding to unitary synaptic currents from one presynaptic cell. Optogenetic stimulation of the striatal indirect pathway axons caused a pause and temporal resetting of the periodic input, confirming that it arose from local neurons subject to striatal inhibition. We determined the firing statistics of the presynaptic neurons from the unitary IPSC statistics and estimated their frequencies, peak amplitudes, and reliabilities. To determine what types of GPe neurons received the spontaneous inhibition, we recorded from genetically labeled parvalbumin (PV) and Npas1 expressing neurons. Both cell types received periodic spontaneous IPSCs with similar frequencies. Optogenetic inhibition of PV neurons reduced the spontaneous IPSC rate in almost all neurons with active unitary inputs, whereas inhibition of Npas1 neurons rarely affected the spontaneous IPSC rate in any neurons. These results suggest that PV neurons provided most of the active unitary inputs to both cell types. Optogenetic pulse stimulation of PV neurons at light levels that can activate cut axons yielded an estimate of connectivity in the fully connected network. The local network is a powerful source of inhibition to both PV and Npas1 neurons, that contributes to irregular firing and may influence the responses to external synaptic inputs.

Clmp Regulates AMPA and Kainate Receptor Responses in the Neonatal Hippocampal CA3 and Kainate Seizure Susceptibility in Mice

Synaptic adhesion molecules regulate synapse development through trans-synaptic adhesion and assembly of diverse synaptic proteins. Many synaptic adhesion molecules positively regulate synapse development; some, however, exert negative regulation, although such cases are relatively rare. In addition, synaptic adhesion molecules regulate the amplitude of post-synaptic receptor responses, but whether adhesion molecules can regulate the kinetic properties of post-synaptic receptors remains unclear. Here we report that Clmp, a homophilic adhesion molecule of the Ig domain superfamily that is abundantly expressed in the brain, reaches peak expression at a neonatal stage (week 1) and associates with subunits of AMPA receptors (AMPARs) and kainate receptors (KARs). Clmp deletion in mice increased the frequency and amplitude of AMPAR-mediated miniature excitatory post-synaptic currents (mEPSCs) and the frequency, amplitude, and decay time constant of KAR-mediated mEPSCs in hippocampal CA3 neurons. Clmp deletion had minimal impacts on evoked excitatory synaptic currents at mossy fiber-CA3 synapses but increased extrasynaptic KAR, but not AMPAR, currents, suggesting that Clmp distinctly inhibits AMPAR and KAR responses. Behaviorally, Clmp deletion enhanced novel object recognition and susceptibility to kainate-induced seizures, without affecting contextual or auditory cued fear conditioning or pattern completion-based contextual fear conditioning. These results suggest that Clmp negatively regulates hippocampal excitatory synapse development and AMPAR and KAR responses in the neonatal hippocampal CA3 as well as object recognition and kainate seizure susceptibility in mice.