Synaptic Gating Research Articles

Firing rate models for gamma oscillations in I-I and E-I networks.

Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional Wilson-Cowan-like models, even when extended to include an explicit dynamic synaptic activation variable, are found unable to capture some dynamics such as Interneuronal Network Gamma oscillations (ING). Use of an explicit delay is helpful in simulations at the expense of complicating mathematical analysis. We resolve this issue by introducing a dynamic variable, u, that acts as an effective delay in the negative feedback loop between firing rate (r) and synaptic gating of inhibition (s). In effect, u endows synaptic activation with second order dynamics. With linear stability analysis, numerical branch-tracking and simulations, we show that our r-u-s rate model captures some key qualitative features of spiking network models for ING. We also propose an alternative formulation, a v-u-s model, in which mean membrane potential v satisfies an averaged current-balance equation. Furthermore, we extend the framework to E-I networks. With our six-variable v-u-s model, we demonstrate in firing rate models the transition from Pyramidal-Interneuronal Network Gamma (PING) to ING by increasing the external drive to the inhibitory population without adjusting synaptic weights. Having PING and ING available in a single network, without invoking synaptic blockers, is plausible and natural for explaining the emergence and transition of two different types of gamma oscillations.

Fatty acid binding proteins are novel modulators of synaptic epoxyeicosatrienoic acid signaling in the brain

Fatty acid binding proteins (FABPs) govern intracellular lipid transport to cytosolic organelles and nuclear receptors. More recently, FABP5 has emerged as a key regulator of synaptic endocannabinoid signaling, suggesting that FABPs may broadly regulate the signaling of neuroactive lipids in the brain. Herein, we demonstrate that brain-expressed FABPs (FABP3, FABP5, and FABP7) interact with epoxyeicosatrienoic acids (EETs) and the peroxisome proliferator-activated receptor gamma agonist 15-deoxy-Δ12,14-Prostaglandin J2 (15d-PGJ2). Among these lipids, EETs displayed highest affinities for FABP3 and FABP5, and 11,12-EET was identified as the preferred FABP ligand. Similarly, 15d-PGJ2 interacted with FABP3 and FABP5 while binding to FABP7 was markedly lower. Molecular modeling revealed unique binding interactions of the ligands within the FABP binding pockets and highlighted major contributions of van der Waals clashes and acyl chain solvent exposure in dictating FABP affinity and specificity. Functional studies demonstrated that endogenous EETs gate the strength of CA1 hippocampal glutamate synapses and that this function was impaired following FABP inhibition. As such, the present study reveals that FABPs control EET-mediated synaptic gating, thereby expanding the functional roles of this protein family in regulating neuronal lipid signaling.

The quarks of attention: Structure and capacity of neural attention building blocks

Attention plays a fundamental role in both natural and artificial intelligence systems. In deep learning, attention-based neural architectures, such as transformer architectures, are widely used to tackle problems in natural language processing and beyond. Here we investigate the most fundamental building blocks of attention and their computational properties within the standard model of deep learning. We first derive a systematic taxonomy of all possible attention mechanisms within, or as extensions of the standard model into 18 classes depending on the origin of the attention signal, the target of the attention signal, and whether the interaction is additive or multiplicative. Second, using this taxonomy, we identify three key attention mechanisms: additive activation attention (multiplexing), multiplicative output attention (output gating), and multiplicative synaptic attention (synaptic gating). Output gating and synaptic gating are proper extensions of the standard model and all current attention-based architectures, including transformers, use either output gating or synaptic gating, or a combination of both. Third, we develop a theory of attention capacity and derive mathematical results about the capacity of basic attention networks comprising linear or polynomial threshold gates. For example, the output gating of a linear threshold gate of n variables by another linear threshold gate of the same n variables has capacity 2n2(1+o(1)), achieving the maximal doubling of the capacity for a doubling of the number of parameters. Perhaps surprisingly, multiplexing attention is used in the proofs of these results. Synaptic and output gating provide computationally efficient extensions of the standard model enabling sparse quadratic activation functions. They can also be viewed as primitives for collapsing several layers of processing in the standard model into shallow compact representations.

STSC-SNN: Spatio-Temporal Synaptic Connection with temporal convolution and attention for spiking neural networks.

Spiking neural networks (SNNs), as one of the algorithmic models in neuromorphic computing, have gained a great deal of research attention owing to temporal information processing capability, low power consumption, and high biological plausibility. The potential to efficiently extract spatio-temporal features makes it suitable for processing event streams. However, existing synaptic structures in SNNs are almost full-connections or spatial 2D convolution, neither of which can extract temporal dependencies adequately. In this work, we take inspiration from biological synapses and propose a Spatio-Temporal Synaptic Connection SNN (STSC-SNN) model to enhance the spatio-temporal receptive fields of synaptic connections, thereby establishing temporal dependencies across layers. Specifically, we incorporate temporal convolution and attention mechanisms to implement synaptic filtering and gating functions. We show that endowing synaptic models with temporal dependencies can improve the performance of SNNs on classification tasks. In addition, we investigate the impact of performance via varied spatial-temporal receptive fields and reevaluate the temporal modules in SNNs. Our approach is tested on neuromorphic datasets, including DVS128 Gesture (gesture recognition), N-MNIST, CIFAR10-DVS (image classification), and SHD (speech digit recognition). The results show that the proposed model outperforms the state-of-the-art accuracy on nearly all datasets.

Differential Activity-Dependent Increase in Synaptic Inhibition and Parvalbumin Interneuron Recruitment in Dentate Granule Cells and Semilunar Granule Cells.

Strong inhibitory synaptic gating of dentate gyrus granule cells (GCs), attributed largely to fast-spiking parvalbumin interneurons (PV-INs), is essential to maintain sparse network activity needed for dentate dependent behaviors. However, the contribution of PV-INs to basal and input-driven sustained synaptic inhibition in GCs and semilunar granule cells (SGCs), a sparse morphologically distinct dentate projection neuron subtype, is currently unknown. In studies conducted in hippocampal slices from mice, we find that although basal IPSCs are more frequent in SGCs and optical activation of PV-INs reliably elicited IPSCs in both GCs and SGCs, optical suppression of PV-INs failed to reduce IPSC frequency in either cell type. Amplitude and kinetics of IPSCs evoked by perforant path (PP) activation were not different between GCs and SGCs. However, the robust increase in sustained polysynaptic IPSCs elicited by paired afferent stimulation was lower in SGCs than in simultaneously recorded GCs. Optical suppression of PV-IN selectively reduced sustained IPSCs in SGCs but not in GCs. These results demonstrate that PV-INs, while contributing minimally to basal synaptic inhibition in both GCs and SGCs in slices, mediate sustained feedback inhibition selectively in SGCs. The temporally selective blunting of activity-driven sustained inhibitory gating of SGCs could support their preferential and persistent recruitment during behavioral tasks.SIGNIFICANCE STATEMENT Our study identifies that feedback inhibitory regulation of dentate semilunar granule cells (SGCs), a sparse and functionally distinct class of projection neurons, differs from that of the classical projection neurons, GCs. Notably, we demonstrate relatively lower activity-dependent increase in sustained feedback inhibitory synaptic inputs to SGCs when compared with GCs which would facilitate their persistent activity and preferential recruitment as part of memory ensembles. Since dentate GC activity levels during memory processing are heavily shaped by basal and feedback inhibition, the fundamental differences in basal and evoked sustained inhibition between SGCs and GCs characterized here provide a framework to reorganize current understanding of the dentate circuit processing.

Multiscale dynamic mean field (MDMF) model relates resting-state brain dynamics with local cortical excitatory-inhibitory neurotransmitter homeostasis.

Previous computational models have related spontaneous resting-state brain activity with local excitatory–inhibitory balance in neuronal populations. However, how underlying neurotransmitter kinetics associated with E–I balance govern resting-state spontaneous brain dynamics remains unknown. Understanding the mechanisms by virtue of which fluctuations in neurotransmitter concentrations, a hallmark of a variety of clinical conditions, relate to functional brain activity is of critical importance. We propose a multiscale dynamic mean field (MDMF) model—a system of coupled differential equations for capturing the synaptic gating dynamics in excitatory and inhibitory neural populations as a function of neurotransmitter kinetics. Individual brain regions are modeled as population of MDMF and are connected by realistic connection topologies estimated from diffusion tensor imaging data. First, MDMF successfully predicts resting-state functional connectivity. Second, our results show that optimal range of glutamate and GABA neurotransmitter concentrations subserve as the dynamic working point of the brain, that is, the state of heightened metastability observed in empirical blood-oxygen-level-dependent signals. Third, for predictive validity the network measures of segregation (modularity and clustering coefficient) and integration (global efficiency and characteristic path length) from existing healthy and pathological brain network studies could be captured by simulated functional connectivity from an MDMF model.

Extensive Inhibitory Gating of Viscerosensory Signals by a Sparse Network of Somatostatin Neurons.

Integration and modulation of primary afferent sensory information begins at the first terminating sites within the CNS, where central inhibitory circuits play an integral role. Viscerosensory information is conveyed to the nucleus of the solitary tract (NTS) where it initiates neuroendocrine, behavioral, and autonomic reflex responses that ensure optimal internal organ function. This excitatory input is modulated by diverse, local inhibitory interneurons, whose functions are not clearly understood. Here we show that, in male rats, 65% of somatostatin-expressing (SST) NTS neurons also express GAD67, supporting their likely role as inhibitory interneurons. Using whole-cell recordings of NTS neurons, from horizontal brainstem slices of male and female SST-yellow fluorescent protein (YFP) and SST-channelrhodopsin 2 (ChR2)-YFP mice, we quantified the impact of SST-NTS neurons on viscerosensory processing. Light-evoked excitatory photocurrents were reliably obtained from SST-ChR2-YFP neurons (n = 16) and the stimulation-response characteristics determined. Most SST neurons (57%) received direct input from solitary tract (ST) afferents, indicating that they form part of a feedforward circuit. All recorded SST-negative NTS neurons (n = 72) received SST-ChR2 input. ChR2-evoked PSCs were largely inhibitory and, in contrast to previous reports, were mediated by both GABA and glycine. When timed to coincide, the ChR2-activated SST input suppressed ST-evoked action potentials at second-order NTS neurons, demonstrating strong modulation of primary viscerosensory input. These data indicate that the SST inhibitory network innervates broadly within the NTS, with the potential to gate viscerosensory input to powerfully alter autonomic reflex function and other behaviors.SIGNIFICANCE STATEMENT Sensory afferent input is modulated according to state. For example the baroreflex is altered during a stress response or exercise, but the basic mechanisms underpinning this sensory modulation are not fully understood in any sensory system. Here we demonstrate that the neuronal processing of viscerosensory information begins with synaptic gating at the first central synapse with second-order neurons in the NTS. These data reveal that the somatostatin subclass of inhibitory interneurons are driven by visceral sensory input to play a major role in gating viscerosensory signals, placing them within a feedforward circuit within the NTS.

Excitation-inhibition balance regulates the patterning of spinal and cranial inspiratory motor outputs in rats in situ

Spinal phrenic nerve activity (PNA) drives the diaphragm but cranial hypoglossal nerve activity (HNA) also expresses synchronous activity during inspiration. Here, we investigated the effects of local disinhibition (bilateral microinjections of bicuculline) of the nucleus tractus solitarius (NTS), the pre-Bötzinger complex and Bötzinger complex core circuit (pre-BötC/BötC) and the Kölliker-Fuse nuclei (KFn) on the synchronization of PNA and HNA in arterially-perfused brainstem preparations of rats. To quantitatively analyze the bicuculline effects on a putatively distributed inspiratory central pattern generator (i-CPG), we quantified the phase synchronization properties between PNA and HNA. The analysis revealed that bicuculline-evoked local disinhibition significantly reduced the strength of phase synchronization between PNA and HNA at any target site. However, the emergence of desynchronized HNA following disinhibition was more prevalent after NTS or pre-BötC/BötC microinjections compared to the KFn. We conclude that the primary i-CPG is located in a distributed medullary circuit whereas pontine contributions are restricted to synaptic gating of synchronous HNA and PNA.

Sleep deprivation-induced pre- and postsynaptic modulation of orexin neurons

Sleep/wake states are controlled by sleep- and wake-promoting systems, and transitions between states are thought to be regulated by their reciprocal inhibition and homeostatic sleep need. Orexin neurons are known to promote wake maintenance and stabilize the sleep/wake switch. Thus, we asked whether orexin neurons are modulated by homeostatic sleep need. Rats were sleep deprived or left undisturbed to rest for 6 h, then acute brain slices were generated for patch clamp recordings. We found that sleep deprivation increased firing and reduced spike frequency adaptation in response to excitatory drive in orexin neurons. These changes were specific to D-type orexin neurons which, unlike H-type orexin neurons, lack A-type current. In D-type orexin neurons, sleep deprivation decreased afterhyperpolarizing potential, which was associated with increased gain, measured as the slope of the input-output relationship. These effects were mimicked by inhibition of SK channels. Furthermore, sleep deprivation resulted in presynaptic inhibition of excitatory inputs to both D-type and H-type orexin neurons, which preferentially affected sparse synaptic inputs while sparing high frequency synaptic activities. Taken together, our results indicate that sleep deprivation modulates the gain control and synaptic gating in orexin neurons. These pre-and postsynaptic changes would tune orexin neurons to strong wake-promoting excitatory signals, while dampening weak synaptic inputs to allow transition to sleep in the absence of such strong signals. These mechanisms are consistent with a role of orexin neurons not only as a key state stabilizer, but also as a homeostatic wake integrator in the sleep/wake switch.This article is part of the Special Issue entitled ‘Hypothalamic Control of Homeostasis’.

Synaptic gating of viscerosensory signals in the solitary tract nucleus

Inhibitory input at the solitary tract nucleus (NTS) is thought to alter autonomic reflex performance. Somatostatin (SOM) neurons are a class of inhibitory interneuron within the central nervous system and present within the NTS. Here we aimed to quantify the impact inhibition had on vicerosensory signal throughput within the NTS. Using a SOM‐Channel rhodopsin 2‐YFP mouse model, we took whole cell recordings from NTS neurons in horizontal brain stem slices that contained both the NTS and solitary tract (ST). This model allowed the specific activation of the SOM inhibitory network within NTS via ChR2. First we targeted SOM‐ChR2‐YFP positive neurons to characterise LED pulse parameters and assay boundaries. Each LED pulse (465 nm, 10 mW) evoked one action potential regardless of pulse duration (0.5 to 100 ms). We then recorded neurons randomly to determine if they received ST input and/or SOM input. LED pulses evoked consistent action potential dependent IPSCs in recorded neurons. Where all (n=42) exhibited LED‐evoked IPSCs and none exhibited LED‐evoked EPSCs or exhibited ChR2 currents. LED‐evoked IPSC amplitude increased with LED duration indicating converging inhibitory input at these NTS neurons. Combined, these data indicate SOM input to NTS neurons is exclusively inhibitory and that though SOM neurons are relatively sparse, SOM efferents synapse extensively throughout the NTS. Shocks to the solitary tract evoked low jitter EPSCs that identified second order NTS neurons. We demonstrated that almost all randomly sampled neurons were second order. Some SOM‐ChR2‐YFP neurons also received direct ST input and additional inhibitory input from other SOM interneurons. We investigated the neurotransmitters and post synaptic receptors involved and find LED‐evoked IPSCs were both GABA and glycine mediated. This finding was surprising as glycinergic transmission has not been described in the medial NTS previously. In current clamp studies, we determined the impact of SOM input on action potential (AP) generation and throughput. LED‐IPSPs prevented spontaneous AP firing when neurons were depolarized and delayed AP onsets in response to current injections. LED‐IPSPs also prevented ST‐evoked AP firing, effectively dropping throughput from 86.7 to 6.7%. Combined, these data indicate that an extensive inhibitory network exists within the NTS that likely operates to coordinate or alter autonomic reflex function.

Nonsmooth Bifurcations of Mean Field Systems of Two-Dimensional Integrate and Fire Neurons

Mean field systems have recently been derived that adequately predict the behaviors of large networks of coupled integrate-and-fire neurons [W. Nicola and S.A. Campbell, J. Comput. Neurosci., 35 (2013), pp. 87--108]. The mean field system for a network of neurons with spike frequency adaptation is typically a pair of differential equations for the mean adaptation and synaptic gating variable of the network. These differential equations are nonsmooth, and, in particular, are piecewise smooth continuous (PWSC). Here, we analyze the smooth and nonsmooth bifurcation structure of these equations and show that the system is organized around a pair of co-dimension-two bifurcations that involve, respectively, the collision between a Hopf equilibrium point and a switching manifold, and a saddle-node equilibrium point and a switching manifold. These two co-dimension-two bifurcations can coalesce into a co-dimension-three nonsmooth bifurcation. As the mean field system we study is a nongeneric piecewise smooth conti...

Behavioral plasticity through the modulation of switch neurons

A central question in artificial intelligence is how to design agents capable of switching between different behaviors in response to environmental changes. Taking inspiration from neuroscience, we address this problem by utilizing artificial neural networks (NNs) as agent controllers, and mechanisms such as neuromodulation and synaptic gating. The novel aspect of this work is the introduction of a type of artificial neuron we call “switch neuron”. A switch neuron regulates the flow of information in NNs by selectively gating all but one of its incoming synaptic connections, effectively allowing only one signal to propagate forward. The allowed connection is determined by the switch neuron’s level of modulatory activation which is affected by modulatory signals, such as signals that encode some information about the reward received by the agent. An important aspect of the switch neuron is that it can be used in appropriate “switch modules” in order to modulate other switch neurons. As we show, the introduction of the switch modules enables the creation of sequences of gating events. This is achieved through the design of a modulatory pathway capable of exploring in a principled manner all permutations of the connections arriving on the switch neurons. We test the model by presenting appropriate architectures in nonstationary binary association problems and T-maze tasks. The results show that for all tasks, the switch neuron architectures generate optimal adaptive behaviors, providing evidence that the switch neuron model could be a valuable tool in simulations where behavioral plasticity is required.

Dynamical estimation of neuron and network properties III: network analysis using neuron spike times.

Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.

Methods for the study of synaptic receptor functional properties.

The generation of a synaptic current at the postsynaptic element (PSCs) is the result of a dynamic sequence of events including the release of the neurotransmitter, its diffusion in the synaptic cleft, and the activation of neurotransmitter receptors located at the postsynaptic side. It is widely accepted that the amplitude and the duration of PSCs are largely dictated by the gating properties of postsynaptic receptors. However, the knowledge of the properties of postsynaptic receptors is mostly derived from steady-state analysis, a condition that is substantially different from the non-equilibrium activation of synaptic receptors imposed by submillisecond neurotransmitter exposures. Given the technical limitations to reproduce the brief "synaptic-like" agonist pulse durations, the functioning of postsynaptic receptors during synaptic transmission is not fully elucidated and the "on-demand" postsynaptic activation of synapses cannot be easily achieved. In this chapter, we review the diverse approaches to study receptor gating at times relevant for synaptic transmission and novel optical/optogenetic techniques for controlling synaptic activity at the postsynaptic level. In addition, we emphasize the role of non-equilibrium in unmasking specific features of synaptic receptor gating and the recent advances in photonics for the light-control of neuronal activity at the single-receptor level.

Synaptic gating at axonal branches, and sharp‐wave ripples with replay: a simulation study

Mechanisms of place cell replay occurring during sharp-wave ripples (SPW-Rs) remain obscure due to the fact that ripples in vitro depend on non-synaptic mechanisms, presumably via axo-axonal gap junctions between pyramidal cells. We suggest a model of in vivo SPW-Rs in which synaptic excitatory post-synaptic potentials (EPSPs) control the axonal spiking of cells in SPW-Rs: ripple activity remains hidden in the network of axonal collaterals (connected by gap junctions) due to conduction failures, unless there is a sufficient dendritic EPSP. The EPSP brings the axonal branching point to threshold, and action potentials from the collateral start to propagate to the soma and to the distal axon. The model coherently explains multiple experimental data on SPW-Rs, both in vitro and in vivo. The mechanism of synaptic gating leads to the following implication: a sequence of pyramidal cells can be replayed at ripple frequency by the superposition of subthreshold dendritic EPSPs and ripple activity in the axonal plexus. Replay is demonstrated in both forward and reverse directions. We discuss several testable predictions. In general, the mechanism of synaptic gating suggests that pyramidal cells under certain conditions can act like a transistor.

Presynaptic Gating of Postsynaptic Synaptic Plasticity

Sensory cortices can not only detect and analyze incoming sensory information but can also undergo plastic changes while learning behaviorally important sensory cues. This experience-dependent cortical plasticity is essential for shaping and modifying neuronal circuits to perform computations of multiple, previously unknown sensations, the adaptive process that is believed to underlie perceptual learning. Intensive efforts to identify the mechanisms of cortical plasticity have provided several important clues; however, the exact cellular sites and mechanisms within the intricate neuronal networks that underlie cortical plasticity have yet to be elucidated. In this review, we present several parallels between cortical plasticity in the auditory cortex and recently discovered mechanisms of synaptic plasticity gating at thalamocortical projections that provide the main input to sensory cortices. Striking similarities between the features and mechanisms of thalamocortical synaptic plasticity and those of experience-dependent cortical plasticity in the auditory cortex, especially in terms of regulation of an early critical period, point to thalamocortical projections as an important locus of plasticity in sensory cortices.

Parsing recursive sentences with a connectionist model including a neural stack and synaptic gating

It is supposed that humans are genetically predisposed to be able to recognize sequences of context-free grammars with centre-embedded recursion while other primates are restricted to the recognition of finite state grammars with tail-recursion. Our aim was to construct a minimalist neural network that is able to parse artificial sentences of both grammars in an efficient way without using the biologically unrealistic backpropagation algorithm. The core of this network is a neural stack-like memory where the push and pop operations are regulated by synaptic gating on the connections between the layers of the stack. The network correctly categorizes novel sentences of both grammars after training. We suggest that the introduction of the neural stack memory will turn out to be substantial for any biological ‘hierarchical processor’ and the minimalist design of the model suggests a quest for similar, realistic neural architectures.

Sensory Over-Responsivity and ADHD: Differentiating Using Electrodermal Responses, Cortisol, and Anxiety.

Deficits in sensory modulation have been linked clinically with impaired attention, arousal, and impulsivity for years, but a clear understanding of the relationship between sensory modulation disorders and attention deficit hyperactivity disorder (ADHD) has proven elusive. Our preliminary work suggested that patterns of salivary cortisol and electrodermal responsivity to sensation may be linked to different groups of children with ADHD; those with and without sensory over-responsivity (SOR). Additionally, SOR has been linked to anxiety, and anxiety has been linked to ADHD. A clearer understanding of the relationship between anxiety, SOR, and ADHD may support a better understanding of ADHD diagnostic subtypes. We examined neuroendocrine, electrodermal and behavioral characteristics and sought to predict group membership among 6- to 12-year-old children with ADHD and SOR (ADHDs), ADHD and no SOR (ADHDt), and typicals (TYP). Behavioral questionnaires were completed to document SOR and anxiety. Lab testing used a Sensory Challenge Protocol (SCP) with concurrent electrodermal measurement and the collection of cortisol prior to and following the SCP. Results substantiated links between SOR and anxiety, in both TYP and ADHD children. Results suggests that ADHD should be considered in conjunction with anxiety and sensory responsivity; both may be related to bottom-up processing differences, and deficits in prefrontal cortex/hippocampal synaptic gating.

Noradrenergic Modulation of Cortical Networks Engaged in Visuomotor Processing

Both animal and human data suggest that stimulation of the noradrenergic system may influence neuronal excitability in regions engaged in sensory processing and visuospatial attention. We tested the hypothesis that the neural mechanisms subserving motor performance in tasks relying on the visuomotor control of goal-directed hand movements might be modulated by noradrenergic influences. Healthy subjects were stimulated using the selective noradrenaline reuptake inhibitor reboxetine (RBX) in a placebo-controlled crossover design. Functional magnetic resonance imaging and dynamic causal modeling (DCM) were used to assess drug-related changes in blood oxygen level-dependent activity and interregional connectivity while subjects performed a joystick task requiring goal-directed movements. Improved task performance under RBX was associated with increased activity in right visual, intraparietal and superior frontal cortex (premotor/frontal eye field). DCM revealed that the neuronal coupling among these regions was significantly enhanced when subjects were stimulated with RBX. Concurrently, right intraparietal cortex and right superior frontal cortex exerted a stronger driving influence on visuomotor areas of the left hemisphere, including SMA and M1. These effects were independent from task difficulty. The data suggest that stimulating noradrenergic mechanisms may rearrange the functional network architecture within and across the hemispheres, for example, by synaptic gating, thereby optimizing motor behavior.

TARP modulation of synaptic AMPA receptor trafficking and gating depends on multiple intracellular domains

Previous work has established stargazin and its related family of transmembrane AMPA receptor regulatory proteins (TARPs) as auxiliary subunits of AMPA receptors (AMPARs) that control synaptic strength both by targeting AMPARs to synapses through an intracellular PDZ-binding motif and by modulating their gating through an extracellular domain. However, TARPs gamma-2 and gamma-8 differentially regulate the synaptic targeting of AMPARs, despite having identical PDZ-binding motifs. Here, we investigate the structural elements that contribute to this functional difference between TARP subtypes by using domain transplantation and truncation. We identify a component of synaptic AMPAR trafficking that is independent of the TARP C-terminal PDZ-binding motif, and we establish previously uncharacterized roles for the TARP intracellular N terminus, loop, and C terminus in modulating both the trafficking and gating of synaptic AMPARs.