Dependent Synaptic Plasticity Research Articles

Rescue of NMDAR-Dependent Synaptic Plasticity in Fmr1 Knock-Out Mice

Fragile X Syndrome (FXS) is the most common form of inherited intellectual disability and results from a loss of Fragile X mental retardation protein (FMRP). FMRP is important for mRNA shuttling and translational control and binds to proteins important for synaptic plasticity. Like many developmental disorders, FXS is associated with alterations in synaptic plasticity that may impair learning and memory processes in the brain. However, it remains unclear whether FMRP plays a ubiquitous role in synaptic plasticity in all brain regions. We report that a loss of FMRP leads to impairments in N-methyl-D-aspartate receptor (NMDAR)-dependent synaptic plasticity in the dentate gyrus (DG), but not in the cornu ammonis area 1 (CA1) subregion of the hippocampus of adult mice. DG-specific deficits are accompanied by a significant reduction in NMDAR GluN1, GluN2A, and GluN2B subunit levels and reduced serine 831 GluA1 phosphorylation specifically in this region. Importantly, we demonstrate that treatment with NMDAR co-agonists (glycine or D-serine) independently rescue impairments in NMDAR-dependent synaptic plasticity in the DG of the Fragile X mental retardation 1 (Fmr1) knockout mouse. These findings implicate the NMDAR in the pathophysiology of FXS and suggest that indirect agonists of the NMDAR may be a successful therapeutic intervention in FXS.

MGluR5 Ablation in Cortical Glutamatergic Neurons Increases Novelty-Induced Locomotion

The group I metabotropic glutamate receptor 5 (mGluR5) has been implicated in the pathology of various neurological disorders including schizophrenia, ADHD, and autism. mGluR5-dependent synaptic plasticity has been described at a variety of neural connections and its signaling has been implicated in several behaviors. These behaviors include locomotor reactivity to novel environment, sensorimotor gating, anxiety, and cognition. mGluR5 is expressed in glutamatergic neurons, inhibitory neurons, and glia in various brain regions. In this study, we show that deleting mGluR5 expression only in principal cortical neurons leads to defective cannabinoid receptor 1 (CB1R) dependent synaptic plasticity in the prefrontal cortex. These cortical glutamatergic mGluR5 knockout mice exhibit increased novelty-induced locomotion, and their locomotion can be further enhanced by treatment with the psychostimulant methylphenidate. Despite a modest reduction in repetitive behaviors, cortical glutamatergic mGluR5 knockout mice are normal in sensorimotor gating, anxiety, motor balance/learning and fear conditioning behaviors. These results show that mGluR5 signaling in cortical glutamatergic neurons is required for precisely modulating locomotor reactivity to a novel environment but not for sensorimotor gating, anxiety, motor coordination, several forms of learning or social interactions.

Patterned high-frequency stimulation induces a form of long-term depression dependent on GABAA and mACh receptors in the hippocampus

Certain patterns of neural activity can induce N-methyl-d-aspartic acid receptor (NMDAR)-dependent synaptic plasticity, one of the important foundations of memory. Here, we report that a patterned high-frequency stimulation (PHS) induces rat hippocampal long-term depression (LTD) in an NMDAR-independent manner that requires coactivation of GABAARs and muscarinic acetylcholine receptors (mAChRs), and endocytosis of AMPARs. Thus, we disclose that a patterned high-frequency stimulation triggers GABAAR and mAChR-dependent LTD in the hippocampus.

Dynamic Observation of Brain-Like Learning in a Ferroelectric Synapse Device

A brain-like learning function was implemented in an electronic synapse device using a ferroelectric-gate field effect transistor (FeFET). The FeFET was a bottom-gate type FET with a ZnO channel and a ferroelectric Pb(Zr,Ti)O3 (PZT) gate insulator. The synaptic weight, which is represented by the channel conductance of the FeFET, is updated by applying a gate voltage through a change in the ferroelectric polarization in the PZT. A learning function based on the symmetric spike-timing dependent synaptic plasticity was implemented in the synapse device using the multilevel weight update by applying a pulse gate voltage. The dynamic weighting and learning behavior in the synapse device was observed as a change in the membrane potential in a spiking neuron circuit.

Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device

Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.

GluA1 and its PDZ-interaction: A role in experience-dependent behavioral plasticity in the forced swim test

Glutamate receptor dependent synaptic plasticity plays an important role in the pathophysiology of depression. Hippocampal samples from clinically depressed patients display reduced mRNA levels for GluA1, a major subunit of AMPA receptors. Moreover, activation and synaptic incorporation of GluA1-containing AMPA receptors are required for the antidepressant-like effects of NMDA receptor antagonists. These findings argue that GluA1-dependent synaptic plasticity might be critically involved in the expression of depression. Using an animal model of depression, we demonstrate that global or hippocampus-selective deletion of GluA1 impairs expression of experience-dependent behavioral despair. This impairment is mediated by the interaction of GluA1 with PDZ-binding domain proteins, as deletion of the C-terminal leucine alone is sufficient to replicate the behavioral phenotype. Our results provide evidence for a significant role of hippocampal GluA1-containing AMPA receptors and their PDZ-interaction in experience-dependent expression of behavioral despair and link mechanisms of hippocampal synaptic plasticity with behavioral expression of depression.

Matrix metalloproteinase dependent cleavage of cell adhesion molecules in the pathogenesis of CNS dysfunction with HIV and methamphetamine.

Physiologically appropriate levels of matrix metalloproteinases (MMPs) are likely important to varied aspects of CNS function. In particular, these enzymes may contribute to neuronal activity dependent synaptic plasticity and to cell mobility in processes including stem cell migration and immune surveillance. Levels of MMPs may, however, be substantially increased in the setting of HIV infection with methamphetamine abuse. Elevated MMP levels might in turn influence integrity of the blood brain barrier, as has been demonstrated in published work. Herein we suggest that elevated levels of MMPs can also contribute to microglial activation as well as neuronal and synaptic injury through a mechanism that involves cleavage of specific cell and synaptic adhesion molecules.

Impaired social memories in 129P2 inbred mice are rescued by reduced Csk expression

The C-terminal Src kinase (Csk) is an essential signaling factor guiding central nervous system (CNS) development. In the adult brain, Csk-mediated control of Src may also modulate glutamatergic synaptic transmission and N-methyl-d-aspartate receptor (NMDAR)-dependent synaptic plasticity. The regulation of N-methyl-d-aspartate (NMDA)-dependent plasticity by a myriad of kinase cascades has been investigated intensively during spatial and fear learning, while little is known about the regulatory kinases and role of NMDA-dependent plasticity during equally critical forms of social learning. We assessed social memory in Csk(+/+) and Csk(+/-) mice backcrossed onto 129P2, an inbred strain with wild-type impairments in social memory. Reduced Csk expression in Csk(+/-) mice was associated with increased NMDAR subunit 2B (NR2B) phosphorylation in the amygdala (AM) and olfactory bulb (OB), and with markedly improved social recognition memory and social transmission of food preference (STFP). In contrast, phosphorylation of NR2B was only slightly increased in the hippocampus of 129P2/Csk(+/-) mice, and the poor spatial object recognition memory of wild-type 129P2/Csk(+/+) mice was not rescued by reduced Csk expression. The Csk pathway appears to be a critical signaling cascade regulating social learning and memory, and presents a possible therapeutic target in diseases such as autism that are characterized by aberrant social behaviors.

Depression-Biased Reverse Plasticity Rule Is Required for Stable Learning at Top-Down Connections

Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body.

Policy gradient rules for populations of spiking neurons

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions given a high neuronal variability. Here, we present two general recipes to derive learning rules from a policy gradient approach for different neural codes and decision making networks, one based on partial integration across feature values, and one based on linear approximation around a target feature. The first technique leads to a tightly code-specific learning rule where details of the code-irrelevant spiking information are integrated away and the code-specificity enters at the synaptic level. The second technique yields modular learning rules which can be weakly code-specific, with a spike-timing dependent base synaptic plasticity rule which is modulated by a code specific population and decision signal. Decisions can be binary, multi-valued, or even continuous-valued. For illustration, we consider a spike count and a spike latency code. We test them on simple model problems and assess the superiority of tight over weak code-specificity with respect to the performance. While code-specific rules increase the performance only marginally when considering a single neuron [1], our tightly code-specific rule designed for population coding can strongly boost performance. Both code-specific learning rules improve in performance with increasing population size as opposed to standard reinforcement learning [2]. For mathematical clarity we presented the rules for an episodic learning scenario. But a biological plausible implementation of a fully online scheme is also possible [2,3].

Dependence of spatial filtering by spike timing dependent synaptic plasticity on learning window

Spike timing dependent synaptic plasticity (STDP) plays an important role in temporal information processing. Whereas our result of the previous study showed that an interconnected network with STDP plays a role in spatial information processing [1]. The role is spatial filtering. In the present study, we studied the effect of learing window of STDP on spatial filtering by the interconnected network with STDP using computer simulation. STDP learning is domated by learning window. Various types of learning window of STDP are found in various brain. In a hippocampus, a post-before-presynaptic spike pair couses synaptic efficacy to strengthen and a pre-before-postsynaptic spike pair courses synaptic efficacy to weaken (here we called this type learning “hippocampal type learning”). In a electrosensory lobe of an electric fish, the learning of STDP is reverse of hippocampal type learning (here we called “electric fish type learning”). Using the learning window of hippocampal type, the network acted as spatial high-contrast filtering. Left figure of Fig.3 shows input image. Neuron on white and grey area receives high and low magnitude of input current, respectively. Middle figure in Fig.3 shows output image from the network. The output image means firing count of neurons of the network from 9000msec to 10000msec. In this case, firing count of neurons which received lower and higher input is lower and larger, respectively. Thus the network with STDP functioned as spatial high contrast filtering using learning window of hippocampal type . Using the learning window of electric fish type, the network acted as spatial low-pass filter. Left figure of Fig.3 shows input image. Right figure of Fig.3 shows output image from the network. The output image means firing count of neurons of the network from 9000msec to 10000msec. In this case, spatial high frequency component was reduced and spatial low frequency component is enhanced in output. Thus the network functioned as spatial low-pass filter using learning window of electric fish type. Figure 1 Left figure is an input image. Middle figure is output of the network with STDP applied hippocampal type learning window. Right figure is output of the network with STDP applied electric fish type learning window. A function of spatial filtering was provided by an interconnected network with STDP. The function changed according to a type of learning window of STDP. In the preset study, we proposed two type of spatial filtering using two type of learning window. The spatial filtering was achieved by dynamically changing connection of the network based on STDP. The results of this study suggested that the interconnected network with STDP might provide appropriate spatial filtering for an optional image from changing network connection according to the image.

Nuclear Translocation of Jacob in Hippocampal Neurons after Stimuli Inducing Long-Term Potentiation but Not Long-Term Depression

BackgroundIn recent years a number of potential synapto-nuclear protein messengers have been characterized that are thought to be involved in plasticity-related gene expression, and that have the capacity of importin- mediated and activity-dependent nuclear import. However, there is a surprising paucity of data showing the nuclear import of such proteins in cellular models of learning and memory. Only recently it was found that the transcription factor cyclic AMP response element binding protein 2 (CREB2) transits to the nucleus during long-term depression (LTD), but not during long-term potentiation (LTP) of synaptic transmission in hippocampal primary neurons. Jacob is another messenger that couples NMDA-receptor-activity to nuclear gene expression. We therefore aimed to study whether Jacob accumulates in the nucleus in physiological relevant models of activity-dependent synaptic plasticity.Methodology/Principal FindingsWe have analyzed the dynamics of Jacob's nuclear import following induction of NMDA-receptor dependent LTP or LTD at Schaffer collateral-CA1 synapses in rat hippocampal slices. Using time-lapse imaging of neurons expressing a Jacob-Green-Fluorescent-Protein we found that Jacob rapidly translocates from dendrites to the nucleus already during the tetanization period of LTP, but not after induction of LTD. Immunocytochemical stainings confirmed the nuclear accumulation of endogenous Jacob in comparison to apical dendrites after induction of LTP but not LTD. Complementary findings were obtained after induction of NMDA-receptor dependent chemical LTP and LTD in hippocampal primary neurons. However, in accordance with previous studies, high concentrations of NMDA and glycine as well as specific activation of extrasynaptic NMDA-receptors resembling pathological conditions induce an even more profound increase of nuclear Jacob levels.Conclusions/SignificanceTaken together, these findings suggest that the two major forms of NMDA-receptor dependent synaptic plasticity, LTP and LTD, elicit the transition of different synapto-nuclear messengers albeit in both cases importin-mediated retrograde transport and NMDA-receptor activation is required.

Dopamine-Signaled Reward Predictions Generated by Competitive Excitation and Inhibition in a Spiking Neural Network Model

Dopaminergic neurons in the mammalian substantia nigra display characteristic phasic responses to stimuli which reliably predict the receipt of primary rewards. These responses have been suggested to encode reward prediction-errors similar to those used in reinforcement learning. Here, we propose a model of dopaminergic activity in which prediction-error signals are generated by the joint action of short-latency excitation and long-latency inhibition, in a network undergoing dopaminergic neuromodulation of both spike-timing dependent synaptic plasticity and neuronal excitability. In contrast to previous models, sensitivity to recent events is maintained by the selective modification of specific striatal synapses, efferent to cortical neurons exhibiting stimulus-specific, temporally extended activity patterns. Our model shows, in the presence of significant background activity, (i) a shift in dopaminergic response from reward to reward-predicting stimuli, (ii) preservation of a response to unexpected rewards, and (iii) a precisely timed below-baseline dip in activity observed when expected rewards are omitted.

Neuronal and microglial mechanisms of neuropathic pain

Neuropathic pain is generally defined as a chronic pain state resulting from peripheral and/or central nerve injury. Effective treatment for neuropathic pain is still lacking, due in part to poor understanding of pathological mechanisms at the molecular level. Neuronal mechanisms of neuropathic pain, especially synaptic plasticity, are the major focus of many investigators. N-methyl-D-aspartate (NMDA) receptor dependent synaptic plasticity at the spinal and cortical levels is believed to contribute to enhanced sensory responses after injury. Glial cells, including astrocytes and microglia, have recently been implicated in neuropathic pain. These glial cells form close interactions with neurons and thus may modulate nociceptive transmission under pathological conditions. In this review, we present recent progress in the study of neuronal and microglial mechanisms underlying neuropathic pain. We propose that activity-dependent neuronal plasticity is a key target for treatment in neuropathic pain.

Functional Interactions in Hierarchically Organized Neural Networks Studied with Spatiotemporal Firing Patterns and Phase-Coupling Frequencies

A scalable hardware/software hybrid module--called Ubidule--endowed with bio-inspired ontogenetic and epigenetic features is configured to run a neural networks simulation with developmental and evolvable capabilities. We simulated the activity of hierarchically organized spiking neural networks characterized by an initial developmental phase featuring cell death followed by spike timing dependent synaptic plasticity in presence of background noise. An upstream 'sensory' network received a spatiotemporally organized external input and downstream networks were activated only via the upstream network. Precise firing sequences, formed by recurrent patterns of spikes intervals above chance levels, were observed in all recording conditions, thus suggesting the build-up of a connectivity able to sustain temporal information processing. The activity of a Ubinet--a network of Ubidules--is analyzed by means of virtual electrodes that recorded neural signals similar to EEG. The analysis of these signals was compared with a small set of human recordings and revealed common patterns of shift in quadratic phase coupling. The results suggest some interpretations of changes and plasticity of functional interactions between cortical areas driven by external stimuli and by learning/cognitive

Calcium Dysregulation and Homeostasis of Neural Calcium in the Molecular Mechanisms of Neurodegenerative Diseases Provide Multiple Targets for Neuroprotection

The intracellular free calcium concentration subserves complex signaling roles in brain. Calcium cations (Ca(2+)) regulate neuronal plasticity underlying learning and memory and neuronal survival. Homo- and heterocellular control of Ca(2+) homeostasis supports brain physiology maintaining neural integrity. Ca(2+) fluxes across the plasma membrane and between intracellular organelles and compartments integrate diverse cellular functions. A vast array of checkpoints controls Ca(2+), like G protein-coupled receptors, ion channels, Ca(2+) binding proteins, transcriptional networks, and ion exchangers, in both the plasma membrane and the membranes of mitochondria and endoplasmic reticulum. Interactions between Ca(2+) and reactive oxygen species signaling coordinate signaling, which can be either beneficial or detrimental. In neurodegenerative disorders, cellular Ca(2+)-regulating systems are compromised. Oxidative stress, perturbed energy metabolism, and alterations of disease-related proteins result in Ca(2+)-dependent synaptic dysfunction, impaired plasticity, and neuronal demise. We review Ca(2+) control processes relevant for physiological and pathophysiological conditions in brain tissue. Dysregulation of Ca(2+) is decisive for brain cell death and degeneration after ischemic stroke, long-term neurodegeneration in Alzheimer's disease, Parkinson's disease, Huntington's disease, inflammatory processes, such as in multiple sclerosis, epileptic sclerosis, and leucodystrophies. Understanding the underlying molecular processes is of critical importance for the development of novel therapeutic strategies to prevent neurodegeneration and confer neuroprotection.

Addicts Lose Plasticity

Loss of glutamate receptor–dependent synaptic plasticity in the brain is associated with the transition to cocaine addiction.

Plasticity resembling spike-timing dependent synaptic plasticity: the evidence in human cortex

Spike-timing dependent plasticity (STDP) has been studied extensively in a variety of animal models during the past decade but whether it can be studied at the systems level of the human cortex has been a matter of debate. Only recently newly developed non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) have made it possible to induce and assess timing dependent plasticity in conscious human subjects. This review will present a critical synopsis of these experiments, which suggest that several of the principal characteristics and molecular mechanisms of TMS-induced plasticity correspond to those of STDP as studied at a cellular level. TMS combined with a second phasic stimulation modality can induce bidirectional long-lasting changes in the excitability of the stimulated cortex, whose polarity depends on the order of the associated stimulus-evoked events within a critical time window of tens of milliseconds. Pharmacological evidence suggests an NMDA receptor mediated form of synaptic plasticity. Studies in human motor cortex demonstrated that motor learning significantly modulates TMS-induced timing dependent plasticity, and, conversely, may be modulated bidirectionally by prior TMS-induced plasticity, providing circumstantial evidence that long-term potentiation-like mechanisms may be involved in motor learning. In summary, convergent evidence is being accumulated for the contention that it is now possible to induce STDP-like changes in the intact human central nervous system by means of TMS to study and interfere with synaptic plasticity in neural circuits in the context of behavior such as learning and memory.

An Active Hardware Dendrite Model Capable of Inducing STDP

The brains of living organisms have excellent information-processing functions. Although various neuron models and artificial neural networks have been investigated, the information processing functions of biological neural networks have not yet been clarified. Recently, various research efforts have confirmed that dendrites perform an important role in brain information processing. Reportedly, STDP (Spike Timing Dependent synaptic Plasticity) is generated between inputs of pre-synaptic neurons and backpropagation of the active potential from dendrites of post-synaptic neuron, as revealed by physiological experiments. Using electronic circuits, we are constructing a hardware model with the characteristics of biological neurons.In this paper, we propose an active hardware dendrite model inducing STDP based on backpropagation phenomena of biological dendrites. Results clarified the following two points.1. The synaptic transmission efficiency of constructed model is changed by timing of the action potential of the input of pre-synaptic neuron and the action potential of backpropagation of the dendrite of the post-synaptic neuron.2. When Δt is small, the amplitude change becomes large. When Δt is large, the amplitude change becomes small

Electrophysiological and molecular mechanisms of synaptic plasticity in the striatum: multi-scale simulation of molecule and cell

Event Abstract Back to Event Electrophysiological and molecular mechanisms of synaptic plasticity in the striatum: multi-scale simulation of molecule and cell Takashi Nakano1*, Junichiro Yoshimoto1, Jeff Wickens1 and Kenji Doya1 1 Okinawa Institute of Science and Technology, Japan The striatum receives glutamatergic input from the cortex and dopaminergic input from the substantia nigra. These inputs, acting together, induce long-term change of corticostriatal synaptic strength, which plays a critical role in learning from reward. Although a number of laboratories have investigated corticostriatal synaptic plasticity, contradictory results and properties have been reported and it is difficult to elucidate the dependence of corticostriatal synaptic plasticity on dopamine, as well as the timing of presynaptic inputs and spike output only by experimentation. To clarify electrophysiological and molecular mechanisms behind the plasticity of striatal synapses, we have constructed models of medium spiny neurons at cellular and molecular levels: an electric compartmental model with a realistic cell morphology (Nakano et al., 2009), and a molecular signaling pathway model (Nakano et al., 2010). These two models operate at different time scales and spatial scales. There are interactions between the two levels. For example, the activation of a postsynaptic signaling cascade is affected by the whole cell electric activity. This makes it difficult to understand the mechanisms only by single models and we need to construct a multi-scale model. In this study, we connected the two models serially, as shown by the solid line in the Figure. First, we constructed an electric compartment model with realistic morphology obtained from our experiments, to investigate the glutamate and dopamine timing effects on the calcium responses and its electrophysiological mechanisms. The parameters were adjusted based on electrophysiological data. The model prediction was that the calcium response is maximal when the glutamate input leads the postsynaptic spike, and that this spike-timing-dependent calcium response was facilitated when the dopamine preceded the glutamate. This suggests the possibility that dopamine timing regulates corticostriatal spike-timing dependent synaptic plasticity (STDP) through its effect on the calcium response. Second, we constructed a signaling pathway model of synaptic spines expressing D1-type dopamine receptors and examined the mechanisms of dopamine- and calcium-dependent plasticity. The model predicted the synaptic changes induced by dopamine and calcium inputs. The positive feedback loop including dopamine- and cAMP-regulated phosphoprotein of molecular weight 32 kDa (DARPP-32) shows bistability and its activation by dopamine input induces dopamine dependent long-term potentiation (LTP). Calcium input alone also caused synaptic efficacy change through several pathways as CaMKII and PP1. The model predicted that the timing of calcium and dopamine inputs has only minor effect on the synaptic change. Finally, by connecting the two models, we predicted synaptic efficacy change induced by a variety of strength and timing of glutamate and dopamine inputs. Although dopamine modulation of channels and receptors is mediated through signaling cascades (blue dashed line in the figure), here, for simplicity, we used output of the electric compartment model as a calcium input for the signaling cascade model. To connect two models, the output data from the electric compartment model was fed as the input to the cascade model. The model reproduced some types of synaptic plasticity which were reported by experiments: 1) High-frequency stimulation (HFS) induces calcium influx, which leads to long-term depression (LTD). 2) HFS in up-state induces a strong calcium response and LTP. 3) LTP is also induced by HFS with dopamine input. 4) STDP is reproduced when NMDA receptors currents are enhanced. The major new findings from the combined system were that the time integral of the calcium response is a good indicator of the synaptic plasticity and that the major effect of the dopamine timing is through its modulation of the calcium response rather than through the temporal response of the molecular signaling cascade.