Computational and Molecular Properties of Starburst Amacrine Cell Synapses Differ With Postsynaptic Cell Type

A presynaptic neuron can increase its computational capacity by transmitting functionally distinct signals to each of its postsynaptic cell types. To determine whether such computational specialization occurs over fine spatial scales within a neurite arbor, we investigated computation at output synapses of the starburst amacrine cell (SAC), a critical component of the classical direction-selective (DS) circuit in the retina. The SAC is a non-spiking interneuron that co-releases GABA and acetylcholine and forms closely spaced (<5 μm) inhibitory synapses onto two postsynaptic cell types: DS ganglion cells (DSGCs) and neighboring SACs. During dynamic optogenetic stimulation of SACs in mouse retina, whole-cell recordings of inhibitory postsynaptic currents revealed that GABAergic synapses onto DSGCs exhibit stronger low-pass filtering than those onto neighboring SACs. Computational analyses suggest that this filtering difference can be explained primarily by presynaptic properties, rather than those of the postsynaptic cells per se. Consistent with functionally diverse SAC presynapses, blockade of N-type voltage-gated calcium channels abolished GABAergic currents in SACs but only moderately reduced GABAergic and cholinergic currents in DSGCs. These results jointly demonstrate how specialization of synaptic outputs could enhance parallel processing in a compact interneuron over fine spatial scales. Moreover, the distinct transmission kinetics of GABAergic SAC synapses are poised to support the functional diversity of inhibition within DS circuitry.

Effect of palmitoylation on the dimer formation of the human dopamine transporter

The human dopamine transporter (hDAT) is one in three members of the monoamine transporter family (MAT). hDAT is essential for regulating the dopamine concentration in the synaptic cleft through dopamine reuptake into the presynaptic neuron; thereby controlling hDAT dopamine signaling. Dysfunction of the transporter is linked to several psychiatric disorders. hDAT and the other MATs have been shown to form oligomers in the plasma membrane, but only limited data exists on which dimeric and higher order oligomeric states are accessible and energetically favorable. In this work, we present several probable dimer conformations using computational coarse-grained self-assembly simulations and assess the relative stability of the different dimer conformations using umbrella sampling replica exchange molecular dynamics. Overall, the dimer conformations primarily involve TM9 and/or TM11 and/or TM12 at the interface. Furthermore, we show that a palmitoyl group (palm) attached to hDAT on TM12 modifies the free energy of separation for interfaces involving TM12, suggesting that S-palmitoylation may change the relative abundance of dimers involving TM12 in a biological context. Finally, a comparison of the identified interfaces of hDAT and palmitoylated hDAT to the human serotonin transporter interfaces and the leucine transporter interface, suggests similar dimer conformations across these protein family.

Synaptic counts approximate synaptic contact area in Drosophila

The pattern of synaptic connections among neurons defines the circuit structure, which constrains the computations that a circuit can perform. The strength of synaptic connections is costly to measure yet important for accurate circuit modeling. It has been shown that synaptic surface area correlates with synaptic strength, yet in the emerging field of connectomics, most studies rely instead on the counts of synaptic contacts between two neurons. Here we quantified the relationship between synaptic count and synaptic area as measured from volume electron microscopy of the larval Drosophila central nervous system. We found that the total synaptic surface area, summed across all synaptic contacts from one presynaptic neuron to a postsynaptic one, can be accurately predicted solely from the number of synaptic contacts, for a variety of neurotransmitters. Our findings support the use of synaptic counts for approximating synaptic strength when modeling neural circuits.

Spiking Neural P Systems with Delay on Synapses

Based on the feature and communication of neurons in animal neural systems, spiking neural P systems (SN P systems) were proposed as a kind of powerful computing model. Considering the length of axons and the information transmission speed on synapses, SN P systems with delay on synapses (SNP-DS systems) are proposed in this work. Unlike the traditional SN P systems, where all the postsynaptic neurons receive spikes at the same instant from their presynaptic neuron, the postsynaptic neurons in SNP-DS systems would receive spikes at different instants, depending on the delay time on the synapses connecting them. It is proved that the SNP-DS systems are universal as number generators. Two small universal SNP-DS systems, with standard or extended rules, are constructed to compute functions, using 56 and 36 neurons, respectively. Moreover, a simulator has been provided, in order to check the correctness of these two SNP-DS systems, thus providing an experimental validation of the universality of the systems designed.

A novel parallel clock-driven algorithm for simulation of neuronal networks based on virtual synapse

The traditional clock-driven algorithm is very time-consuming when performed on large-scale neuronal networks due to the huge number of synaptic currents computation and low performance of the parallel implementation of the algorithm. We find in this paper that the conductance coefficients of all the synapses coming from the same presynaptic neuron (neuron [Formula: see text] for example) does not need to be computed one by one, rather only one common conductance coefficient needs to be computed for all synapses from this neuron. We then propose an idea of virtual synapse for neuron [Formula: see text] to compute this common conductance coefficient and thereby have [Formula: see text] ([Formula: see text] is the number of neurons in the network) virtual synapses for all presynaptic neurons in the network. Since each common conductance depends on only the spiking activity of the presynaptic neuron [Formula: see text] and is irrelevant of postsynaptic neurons, the computation of the different virtual synapses can be deployed to different computer processing unit efficiently. By introducing a circular data structure for the virtual synapses, we present a novel parallel clock-driven algorithm based on graphics processors for simulation of neuronal networks. It is demonstrated by test results that the proposed algorithm reduces memory and time consumption greatly, and improves the performance of the parallelization for large-scale neuronal network simulations effectively.

Sleep-like behavior is a fundamental property of the tripartite synapse

The tripartite synapse, consisting of the presynaptic neuron, post-synaptic neuron, and an astrocyte, is considered to be the main locus of signaling between neurons in the brain.1,2 Neurotransmission is energetically very expensive3,4, and the primary neurotransmitter utilized for signaling is glutamate. It has been found that glutamate is also used as a substrate for energy generation.5,6 However, it is unclear what the relationship is between energy generation and availability of neurotransmitter during glutamatergic neurotransmission. Here we show that availability of energy, represented by adenosine triphosphate (ATP), and glutamate for neurotransmission are intimately related, and in fact determine the ability to signal at the tripartite synapse. Using a novel neurochemical mathematical model of the tripartite synapse, we found that glutamate concentrations for neurotransmission and ATP concentrations were interdependent, and their interplay controlled the firing pattern of the presynaptic terminal, as defined by synaptic vesicle release. Furthermore, we found that depending on the parameters chosen in the model, the tripartite synapse demonstrated behavior with limit cycles, alternating between high- and low-frequency firing rates. Our results show that complex behavior with high- and low-activity states, qualitatively meeting the characteristics of sleep7 emerges directly from the nature of the tripartite synapse, with glutamate and ATP concentrations serving as the signals for state changes. We anticipate that our model will serve as a starting point to further elucidate the energetics of neuronal and brain functioning, and eventually shed light on the fundamental question of the nature and necessity of sleep.

Presynaptic MAST kinase controls opposing postsynaptic responses to convey stimulus valence in Caenorhabditis elegans

Presynaptic plasticity is known to modulate the strength of synaptic transmission. However, it remains unknown whether regulation in presynaptic neurons can evoke excitatory and inhibitory postsynaptic responses. We report here that the Caenorhabditis elegans homologs of MAST kinase, Stomatin, and Diacylglycerol kinase act in a thermosensory neuron to elicit in its postsynaptic neuron an excitatory or inhibitory response that correlates with the valence of thermal stimuli. By monitoring neural activity of the valence-coding interneuron in freely behaving animals, we show that the alteration between excitatory and inhibitory responses of the interneuron is mediated by controlling the balance of two opposing signals released from the presynaptic neuron. These alternative transmissions further generate opposing behavioral outputs necessary for the navigation on thermal gradients. Our findings suggest that valence-encoding interneuronal activity is determined by a presynaptic mechanism whereby MAST kinase, Stomatin, and Diacylglycerol kinase influence presynaptic outputs.

Distribution and strength of interlaminar synaptic connectivity in mouse primary visual cortex revealed by two-photon optogenetic stimulation

The most common synaptic connections between neurons in different cortical layers form the basis of the canonical cortical microcircuit. Understanding of cortical function will require further development and application of methods to efficiently characterize synaptic connections within and outside of the canonical pathway. Accordingly, we measured synaptic inputs onto superficial excitatory neurons in response to sequential two-photon optogenetic stimulation of neurons in deeper layers. Layer 4 excitatory neurons and somatostatin-neurons within layer 2/3 represented the most common sources of input. Although connections from excitatory and somatostatin-neurons in layer 5 were less common, the amplitudes of synaptic responses were equally strong. We examined synaptic strength across all connections, as well as the relationships between the strength of connections diverging from a common presynaptic neuron or converging to a single target. While the overall distribution indicates synaptic weight is concentrated to a few connections, strong excitatory connections are distributed across cells.

Cell Type-Specific Modulation of Layer 6A Excitatory Microcircuits by Acetylcholine in Rat Barrel Cortex

Acetylcholine (ACh) is known to regulate cortical activity during different behavioral states, e.g. wakefulness and attention. Here we show a differential expression of muscarinic ACh receptors (mAChRs) and nicotinic AChRs (nAChRs) in different layer 6A (L6A) pyramidal cell (PC) types of somatosensory cortex. At low concentrations, ACh induced a persistent hyperpolarization in corticocortical (CC) but a depolarization in corticothalamic (CT) L6A PCs via M4 and M1 mAChRs, respectively. At ∼1 mM ACh depolarized exclusively CT PCs via α4β2 subunit-containing nAChRs without affecting CC PCs. Miniature EPSC frequency in CC PCs was decreased by ACh but increased in CT PCs. In synaptic connections with a presynaptic CC PC, glutamate release was suppressed via M4 mAChR activation but enhanced by nAChRs via α4β2 nAChRs when the presynaptic neuron was a CT PC. Thus, in layer 6A the interaction of mAChRs and nAChRs results in an altered excitability and synaptic release, effectively strengthening corticothalamic output while weakening corticocortical synaptic signaling.

Presynaptic MAST Kinase Controls Bidirectional Post-Synaptic Responses to Convey Stimulus Valence in C. elegans

Presynaptic plasticity is known to modulate the strength of synaptic transmission. However, it remains unknown whether regulation in presynaptic neurons alters the directionality –positive or negative-of postsynaptic responses. We report here that the C. elegans homologs of MAST kinase, Stomatin and Diacylglycerol kinase act in a thermosensory neuron to elicit in its postsynaptic neuron an excitatory or inhibitory response that correlates with the valence of thermal stimuli. By monitoring neural activity of the valence-coding interneuron in freely behaving animals, we show that the alteration between excitatory and inhibitory responses of the interneuron is mediated by controlling the balance of two opposing signals released from the presynaptic neuron. These alternative transmissions further generate opposing behavioral outputs necessary for the navigation on thermal gradients. Our findings reveal the previously unrecognized capability of presynaptic regulation to evoke bidirectional postsynaptic responses and suggest a molecular mechanism of determining stimulus valence.