Controlling morpho-electrophysiological variability of neurons with detailed biophysical models.

Variability, which is known to be a universal feature among biological units such as neuronal cells, holds significant importance, as, for example, it enables a robust encoding of a high volume of information in neuronal circuits and prevents hypersynchronizations. While most computational studies on electrophysiological variability in neuronal circuits were done with single-compartment neuron models, we instead focus on the variability of detailed biophysical models of neuron multi-compartmental morphologies. We leverage a Markov chain Monte Carlo method to generate populations of electrical models reproducing the variability of experimental recordings while being compatible with a set of morphologies to faithfully represent specifi morpho-electrical type. We demonstrate our approach on layer 5 pyramidal cells and study the morpho-electrical variability and in particular, find that morphological variability alone is insufficient to reproduce electrical variability. Overall, this approach provides a strong statistical basis to create detailed models of neurons with controlled variability.

A universal workflow for creation, validation, and generalization of detailed neuronal models.

Detailed single-neuron modeling is widely used to study neuronal functions. While cellular and functional diversity across the mammalian cortex is vast, most of the available computational tools focus on a limited set of specific features characteristic of a single neuron. Here, we present a generalized automated workflow for the creation of robust electrical models and illustrate its performance by building cell models for the rat somatosensory cortex. Each model is based on a 3D morphological reconstruction and a set of ionic mechanisms. We use an evolutionary algorithm to optimize neuronal parameters to match the electrophysiological features extracted from experimental data. Then we validate the optimized models against additional stimuli and assess their generalizability on a population of similar morphologies. Compared to the state-of-the-art canonical models, our models show 5-fold improved generalizability. This versatile approach can be used to build robust models of any neuronal type.

GABAergic-like dopamine synapses in the brain.

Dopamine synapses play a crucial role in volitional movement and reward-related behaviors, while dysfunction of dopamine synapses causes various psychiatric and neurological disorders. Despite this significance, the true biological nature of dopamine synapses remains poorly understood. Here, we show that dopamine transmission is strongly correlated with GABA co-transmission across the brain and dopamine synapses are structured and function like GABAergic synapses with marked regional heterogeneity. In addition, GABAergic-like dopamine synapses are clustered on the dendrites, and GABA transmission at dopamine synapses has distinct physiological properties. Interestingly, the knockdown of neuroligin-2, a key postsynaptic protein at GABAergic synapses, unexpectedly does not weaken GABA co-transmission but instead facilitates it at dopamine synapses in the striatal neurons. More importantly, the attenuation of GABA co-transmission precedes deficits in dopaminergic transmission in animal models of Parkinson's disease. Our findings reveal the spatial and functional nature of GABAergic-like dopamine synapses in health and disease.

Overexpression of UCP4 in astrocytic mitochondria prevents multilevel dysfunctions in a mouse model of Alzheimer's disease.

Alzheimer's disease (AD) is becoming increasingly prevalent worldwide. It represents one of the greatest medical challenges as no pharmacologic treatments are available to prevent disease progression. Astrocytes play crucial functions within neuronal circuits by providing metabolic and functional support, regulating interstitial solute composition, and modulating synaptic transmission. In addition to these physiological functions, growing evidence points to an essential role of astrocytes in neurodegenerative diseases like AD. Early-stage AD is associated with hypometabolism and oxidative stress. Contrary to neurons that are vulnerable to oxidative stress, astrocytes are particularly resistant to mitochondrial dysfunction and are therefore more resilient cells. In our study, we leveraged astrocytic mitochondrial uncoupling and examined neuronal function in the 3xTg AD mouse model. We overexpressed the mitochondrial uncoupling protein 4 (UCP4), which has been shown to improve neuronal survival in vitro. We found that this treatment efficiently prevented alterations of hippocampal metabolite levels observed in AD mice, along with hippocampal atrophy and reduction of basal dendrite arborization of subicular neurons. This approach also averted aberrant neuronal excitability observed in AD subicular neurons and preserved episodic-like memory in AD mice assessed in a spatial recognition task. These findings show that targeting astrocytes and their mitochondria is an effective strategy to prevent the decline of neurons facing AD-related stress at the early stages of the disease.

Different priming states of synaptic vesicles underlie distinct release probabilities at hippocampal excitatory synapses.

A stunning example of synaptic diversity is the postsynaptic target cell-type-dependent difference in synaptic efficacy in cortical networks. Here, we show that CA1 pyramidal cell (PC) to fast spiking interneuron (FSIN) connections have 10-fold larger release probability (Pv) than those on oriens lacunosum-moleculare (O-LM) interneurons. Freeze-fracture immunolabeling revealed that different nano-topologies and coupling distances between Ca2+ channels and release sites (RSs) are not responsible for the distinct Pv. Although [Ca2+] transients are 40% larger in FSINs innervating boutons, when [Ca2+] entry is matched in the two bouton populations, EPSCs in O-LM cells are still 7-fold smaller. However, application of a phorbol ester analog resulted in a ∼2.5-fold larger augmentation at PC - O-LM compared to PC - FSIN synapses, suggesting incomplete docking or priming of vesicles. Similar densities of docked vesicles rule out distinct RS occupancies and demonstrate that incompletely primed, but docked, vesicles limit the output of PC - O-LM synapses.

A first-passage approach to diffusion-influenced reversible binding and its insights into nanoscale signaling at the presynapse.

Synaptic transmission between neurons is governed by a cascade of stochastic calcium ion reaction-diffusion events within nerve terminals leading to vesicular release of neurotransmitter. Since experimental measurements of such systems are challenging due to their nanometer and sub-millisecond scale, numerical simulations remain the principal tool for studying calcium-dependent neurotransmitter release driven by electrical impulses, despite the limitations of time-consuming calculations. In this paper, we develop an analytical solution to rapidly explore dynamical stochastic reaction-diffusion problems based on first-passage times. This is the first analytical model that accounts simultaneously for relevant statistical features of calcium ion diffusion, buffering, and its binding/unbinding reaction with a calcium sensor for synaptic vesicle fusion. In particular, unbinding kinetics are shown to have a major impact on submillisecond sensor occupancy probability and therefore cannot be neglected. Using Monte Carlo simulations we validated our analytical solution for instantaneous calcium influx and that through voltage-gated calcium channels. We present a fast and rigorous analytical tool that permits a systematic exploration of the influence of various biophysical parameters on molecular interactions within cells, and which can serve as a building block for more general cell signaling simulators.

Distinct Nanoscale Calcium Channel and Synaptic Vesicle Topographies Contribute to the Diversity of Synaptic Function.

The nanoscale topographical arrangement of voltage-gated calcium channels (VGCC) and synaptic vesicles (SVs) determines synaptic strength and plasticity, but whether distinct spatial distributions underpin diversity of synaptic function is unknown. We performed single bouton Ca2+ imaging, Ca2+ chelator competition, immunogold electron microscopic (EM) localization of VGCCs and the active zone (AZ) protein Munc13-1, at two cerebellar synapses. Unexpectedly, we found that weak synapses exhibited 3-fold more VGCCs than strong synapses, while the coupling distance was 5-fold longer. Reaction-diffusion modeling could explain both functional and structural data with two strikingly different nanotopographical motifs: strong synapses are composed of SVs that are tightly coupled (∼10 nm) to VGCC clusters, whereas at weak synapses VGCCs were excluded from the vicinity (∼50 nm) of docked vesicles. The distinct VGCC-SV topographical motifs also confer differential sensitivity to neuromodulation. Thus, VGCC-SV arrangements are not canonical, and their diversity could underlie functional heterogeneity across CNS synapses.

Variations in Ca2+ Influx Can Alter Chelator-Based Estimates of Ca2+ Channel-Synaptic Vesicle Coupling Distance.

The timing and probability of synaptic vesicle fusion from presynaptic terminals is governed by the distance between voltage-gated Ca2+ channels (VGCCs) and Ca2+ sensors for exocytosis. This VGCC-sensor coupling distance can be determined from the fractional block of vesicular release by exogenous Ca2+ chelators, which depends on biophysical factors that have not been thoroughly explored. Using numerical simulations of Ca2+ reaction and diffusion, as well as vesicular release, we examined the contributions of conductance, density, and open duration of VGCCs, and the influence of endogenous Ca2+ buffers on the inhibition of exocytosis by EGTA. We found that estimates of coupling distance are critically influenced by the duration and amplitude of Ca2+ influx at active zones, but relatively insensitive to variations of mobile endogenous buffer. High concentrations of EGTA strongly inhibit vesicular release in close proximity (20-30 nm) to VGCCs if the flux duration is brief, but have little influence for longer flux durations that saturate the Ca2+ sensor. Therefore, the diversity in presynaptic action potential duration is sufficient to alter EGTA inhibition, resulting in errors potentially as large as 300% if Ca2+ entry durations are not considered when estimating VGCC-sensor coupling distances.SIGNIFICANT STATEMENT The coupling distance between voltage-gated Ca2+ channels and Ca2+ sensors for exocytosis critically determines the timing and probability of neurotransmitter release. Perfusion of presynaptic terminals with the exogenous Ca2+ chelator EGTA has been widely used for both qualitative and quantitative estimates of this distance. However, other presynaptic terminal parameters such as the amplitude and duration of Ca2+ entry can also influence EGTA inhibition of exocytosis, thus confounding conclusions based on EGTA alone. Here, we performed reaction-diffusion simulations of Ca2+-driven synaptic vesicle fusion, which delineate the critical parameters influencing an accurate prediction of coupling distance. Our study provides guidelines for characterizing and understanding how variability in coupling distance across chemical synapses could be estimated accurately.