Synaptic plasticity, which underlies learning and memory, depends on calcium elevation in neurons, but the precise relationship between calcium and spatiotemporal patterns of synaptic inputs is unclear. Here, we develop a biologically realistic computational model of striatal spiny projection neurons with sophisticated calcium dynamics, based on data from rodents of both sexes, to investigate how spatiotemporally clustered and distributed excitatory and inhibitory inputs affect spine calcium. We demonstrate that coordinated excitatory synaptic inputs evoke enhanced calcium elevation specific to stimulated spines, with lower but physiologically relevant calcium elevation in nearby non-stimulated spines. Results further show a novel and important function of inhibition—to enhance the difference in calcium between stimulated and non-stimulated spines. These findings suggest that spine calcium dynamics encode synaptic input patterns and may serve as a signal for both stimulus-specific potentiation and heterosynaptic depression, maintaining balanced activity in a dendritic branch while inducing pattern-specific plasticity. How do we form new memories? The human brain contains almost 90 billion neurons, which communicate with one another at junctions called synapses. Each neuron has a shape a little like that of a tree, and is covered in branches called dendrites. Synapses typically form between the end of one neuron and a dendrite on another. Most scientists believe that the brain forms new memories by changing the strength of these synapses. But a number of questions remain about how this process works.There are two types of synapses: excitatory and inhibitory. When an excitatory synapse becomes active, calcium ions flow into the dendrite of the receiving neuron. The calcium ions then trigger processes inside the cell that are essential for changing the strength of the synapse, and thus forming a memory. But what happens when an inhibitory synapse becomes active? How does this affect memory?Additionally, each neuron forms synapses with thousands of others, with several synapses on a single dendrite. To form a memory about a specific experience, the brain must strengthen only the synapses that relate to that experience. How does the brain manage to target these synapses specifically? Do the synapses need to be clustered on the same dendritic branch, or can they be spread apart? And do all the synapses need to be active at exactly the same time?Dorman et al. investigated these questions by developing a computer model of a neuron. Testing the model revealed that the synapses related to an experience do not all need to be active at exactly the same time to form a memory. Moreover, the synapses can be spread across multiple dendrites. Finally, the model showed that inhibitory synapses are critical for preventing calcium ions from spreading within dendritic branches and entering inactive synapses. This ensures that only the synapses active during a specific experience become stronger.Many brain disorders, including substance abuse and addiction, involve errors in the processes that underlie learning and memory. By increasing our understanding of how the structure of brain cells supports these processes, the current findings could one day lead to better treatments for these and other disorders. Further, certain patterns of input can induce synaptic plasticity—neural activity-dependent changes in synaptic efficacy that underlie learning and memory. Yet, it remains unclear how spatiotemporal properties of synaptic input patterns may affect synaptic plasticity  and their timing  . As a giasticity .Dendrites are capable of complex, non-linear forms of synaptic integration, which are sensitive to the spatiotemporal properties of synaptic inputs . For insCalcium influx into neuronal dendrites and spines is a critical mechanism linking synaptic input patterns to synaptic plasticity, as calcium is required for most forms of neuronal plasticity throughout the brain . The conSpatiotemporally clustered synaptic inputs that produce supralinear plateau potentials  also cause elevated dendritic calcium concentration localized to the stimulated dendritic branch . In vivoAlthough much of the literature has focused on synaptic integration in pyramidal neurons, NMDAR-dependent plateau potentials also have been observed in the spiny projection neurons (SPNs) of the striatum, which is the input nucleus of the basal ganglia . The strSPNs and pyramidal neurons exhibit key differences which motivate the further study of SPNs. In contrast to pyramidal cells, SPNs lack the morphologically distinct apical, oblique, and basal dendritic branches characteristic of pyramidal neurons . WhereasA kinetics. These distinct sources of inhibition have been shown to regulate plateau potentials in somatic recordings  or distal (135 – 225 μm from soma) regions of a dendritic branch, or over the entire branch . SynaptiSynapse-specificity—that potentiation is limited to only those synapses which actively contribute to a postsynaptic response—is critical for synaptic plasticity to underlie learning and memory. Synapse-specific LTP requires that the elevated calcium concentration is confined to stimulated spines, as opposed to non-stimulated, neighboring spines, during a plateau potential. It is not clear how synapse-specificity is maintained during plateau potentials, when the entire dendritic branch becomes strongly depolarized and experiences calcium elevation as shown in calcium-imaging experiments . The strTo quantify synapse-specificity, we sampled calcium concentration from spines along the entire branch, both proximal and distal spines, including non-stimulated spines located between two stimulated spines for the spatially dispersed condition. In response to synaptic inputs to distal dendritic spines, peak calcium elevation in stimulated spines was an order of magnitude higher than in non-stimulated, neighboring spines. Similarly, when synaptic inputs were spatially dispersed, peak calcium elevation in stimulated spines was again an order of magnitude higher than in non-stimulated, interspersed spines . Thus, cAlthough calcium elevation in non-stimulated spines was significantly smaller than stimulated spines, it was also significantly higher than baseline, although only for a subset of non-stimulated spines. Specifically, only the distally located non-stimulated spines exhibited a calcium elevation, with negligible calcium elevation in proximal non-stimulated spines. This suggests that heterosynaptic effects that may occur during a plateau potential would be limited to neighboring non-stimulated spines located on the distal dendritic branch. This distal-to-proximal gradient in calcium elevation is also observed in the dendritic shaft. Therefore, other calcium-dependent types of plasticity, such as homeostatic scaling or branch strength plasticity, also may occur in the distal dendritic shaft during plateau potentials. In summary, these results show three distinct, spatially specific calcium responses to coordinated distal synaptic inputs: a high, supralinear response in stimulated spines; an intermediate response in non-stimulated distal spines and in the distal dendritic shaft; and a negligible response in proximal non-stimulated spines.Understanding the biological mechanisms controlling differences in calcium dynamics between stimulated and neighboring non-stimulated spines may yield greater insights to synapse-specific signaling. Three different sources of spine calcium elevation—calcium permeable synaptic channels, voltage-gated calcium channels, and diffusion —could enhance or decrease differences in spine calcium concentration between stimulated and non-stimulated spines. To investigate which of these mechanisms distinguishes stimulated spines, we analyzed membrane potential, spine calcium concentration, and calcium channel currents in a stimulated spine and a neighboring non-stimulated spine during clustered distal synaptic stimulation. Additionally, we isolated VGCC-mediated and diffusion-mediated calcium elevations in non-stimulated spines by selectively blocking diffusion between non-stimulated spines and the dendritic shaft.Calcium influx through synaptic channels underlies the high spine calcium elevation specific to stimulated spines. Analysis of spine head membrane potential indicated little difference between stimulated and neighboring non-stimulated spines , indicatVGCCs and diffusion both contribute to calcium elevations in non-stimulated neighboring spines. Blocking diffusion of calcium and calcium buffers between the dendritic shaft and non-stimulated spines reduced the later phase of calcium elevation in non-stimulated spines , indicatTogether, these results indicate that the spatial specificity of calcium elevation results from synaptic calcium influx in stimulated spines, whereas both diffusion and VGCC influx increase calcium concentration in neighboring, non-stimulated spines. Consequently, calcium transients exhibit a robust synapse-specific signal in stimulated spines despite highly similar membrane potentials in neighboring spines during plateau potentials. Further, as membrane potential is sharply attenuated as depolarization propagates towards the soma, the VGCC-mediated elevation is limited to distal non-stimulated spines whereas proximal non-stimulated spines exhibit negligible calcium elevation. The distinct calcium transients and sources observed may therefore support stimulus-specific synaptic plasticity in stimulated spines and heterosynaptic plasticity in neighboring, non-stimulated spines.Synaptic inputs are likely to be spatially and temporally dispersed on multiple dendritic branches in vivo. This raises critical questions: to evoke supralinear spine calcium transients, do cortical inputs need to target a single dendritic branch, or can inputs be spatially dispersed on the entire neuron? Further, would synaptic inputs on multiple branches act independently—such that the number of synaptic inputs per branch required to evoke supralinear calcium transients is independent of synaptic inputs to other branches—or would they interact (cooperate) to lower the threshold number of synaptic inputs per branch required for supralinear calcium transients? To address these questions, we investigated the effect of spatial dispersion of synaptic inputs to multiple dendritic branches. Synaptic inputs were randomly distributed on two tertiary branches with a common secondary branch parent; on four tertiary branches with a common primary branch parent; or on eight tertiary dendritic branches. Additionally, we used both simultaneous synaptic inputs and temporal dispersion, created from random, exponentially distributed intervals. Simulations used average interstimulus intervals (ISIs) of 2.5, 5, or 10 ms between synaptic inputs on each branch  . SpecifyWhen simultaneous synaptic inputs are spatially dispersed across multiple branches, the total number of synaptic inputs required to elicit supralinear spine calcium transients is increased . This inAs the average ISI is increased, there is an overall reduction in supralinear spine calcium elevation. However, when multiple branches are stimulated, increasing the mean ISI up to 5 ms can increase spine calcium elevation, indicating that, with spatial dispersion, a small temporal dispersion increases cooperativity. The corresponding somatic voltage  shows suAltogether, results using spatiotemporally dispersed synaptic inputs suggest that each distal dendritic branch in SPNs may function as a relatively independent subunit for integrating synaptic inputs with spine-specific calcium responses. These results are consistent with the theory that individual dendritic branches serve as critical subunits for synaptic integration and plasticity .The distinct calcium signals in proximal versus distal stimulated spines in response to coordinated synaptic inputs suggests that proximal and distal synapses may have distinct functions in SPNs. This raises the question of whether distal and proximal synapses can interact or instead function independently. Just as a somatic action potential can back-propagate to enhance spine calcium elevation, we investigated whether a cluster of synaptic inputs, in the absence of a somatic action potential, can enhance spine calcium elevation. To test whether a distally evoked plateau potential could interact with a stimulated proximal synapse on the same branch, we paired clustered distal stimulation and single proximal spine stimulation with varying temporal intervals and evaluated the calcium responses in the proximal spine .Our results show that distal clustered synaptic inputs can facilitate calcium elevation in response to synaptic input to proximal spines, dependent on timing. Simultaneous stimulation of a distal cluster and single proximal spine facilitated the proximal spine peak calcium concentration . The simA synapses exhibit distinct spatial organization, with fast spiking interneurons (FSIs) targeting proximal dendrites and low threshold spiking interneurons (LTSIs) and SPN collaterals targeting distal dendrites, and they exhibit distinct temporal kinetics, with neurogliaform (NGF) interneurons exhibiting much slower activation and inactivation time constants  may be particularly potent regulators of dendritic integration and synaptic interactions in SPNs.Additionally, our results show that the timing of GABAergic stimulation relative to clustered glutamatergic stimulation affects the resulting spine calcium elevation . We pairAs FSIs provide strong proximal inhibition to SPNs in vivo, we also investigated whether a train of proximal GABAergic inputs (as opposed to a single input) would affect cooperativity among stimulated spines or between dendritic branches . A trainNotably, although we observed above that inhibition close to excitatory inputs can reduce the magnitude of spine calcium elevation in stimulated spines , inhibition neither abolished the plateau potential nor fully blocked supralinear spine calcium elevation. This raised the intriguing possibility that the reduced local membrane resistance caused by inhibition may also influence non-stimulated spines. Thus, we evaluated the effect of inhibition by measuring the peak calcium response in non-stimulated spines relative to the peak calcium response in stimulated spines in the presence or absence of a co-located and simultaneously stimulated GABAergic synapse during simultaneous excitatory stimulation of a distal cluster of dendritic spines.The most significant functional effect of distal GABAergic synaptic input is to enhance spatial specificity . When coIt is critical in computational modeling to assess the robustness of results to variations in parameter values. To assess the robustness of the effect of inhibition on synapse-specificity, we systematically varied conductances of voltage-gated and synaptic channels, calcium buffer quantities and pump densities, and spine neck axial resistance by ±10% and 20%. For each condition, we computed the specificity ratio as the ratio of peak calcium of non-stimulated spines to peak calcium of stimulated spines, such that a smaller value indicates higher specificity. We then divided the specificity ratio observed with inhibition by the specificity ratio observed without inhibition , such that a value <1 indicates that inhibition enhances specificity, while a value >1 indicates that inhibition reduces specificity. Inhibition consistently enhanced spatial specificity across all parameter variations, except for a 20% decrease in NMDAR conductance . The magIn addition to robustness to parameter variations, it is important that our main result does not depend on underlying assumptions in the modeling method. Specifically, our model of calcium dynamics assumes that deterministic, one-dimensional diffusion and reaction equations are sufficient to capture the dynamics of calcium elevation in dendritic spines. We evaluated whether the following variations affected the central finding that inhibition enhances synapse-specificity: (1) spatial and temporal discretization step size; (2) variations in calcium diffusion rates; (3) facilitated calcium diffusion between spine neck and dendritic shaft; and (4) variations in calcium influx and efflux caused by channels and pumps. Importantly, these findings did not qualitatively change the main result that inhibition enhances spatial specificity .A critical functional question is whether inhibition regulates synaptic specificity for spatiotemporally distributed inputs, which are likely to occur in vivo. To answer this question, we applied both excitatory (n = 200 or 300) and inhibitory (n = 50) synaptic inputs with random spatial dispersion, with each individual synaptic input consisting of an independent Poisson process with an average frequency of 2.5 Hz. We assessed spine calcium with histograms of integrated calcium for the 1 s simulation duration, as well as scatter plots of peak values versus normalized duration  for each spine. At the lower (n = 200) activity level, synaptic specificity was robust with or without inhibition, with little overlap in integrated calcium and no overlap for peak versus duration scatter points . HoweverTo quantify the extent to which inhibition increased separation between stimulated and non-stimulated spine calcium responses, we performed a cluster analysis using duration and peak calcium as parameters. For the cluster analysis, we performed K-means clustering on the unlabeled data, and then computed the confusion matrix—the number of correctly and incorrectly clustered data points in the unlabeled cluster analysis compared to the real, labeled dataset, where the label is whether the spine received synaptic input. We evaluated the number of incorrectly clustered spines in the confusion matrix and computed the distance between clusters as a metric for the effect of inhibition on synaptic specificity. For the higher activity level without inhibition, the cluster analysis incorrectly identified the stimulation status of 58 spines, whereas with inhibition, the stimulation status of only 19 spines was incorrectly identified . For the lower activity level, no spines were incorrectly identified, but inhibition increased the distance between cluster centroids by 5.3%. Altogether, these results suggest that although inhibition reduces calcium elevation in stimulated spines, its most significant effect is to enhance stimulus-specific calcium signaling and it may therefore regulate heterosynaptic plasticity.We demonstrated that spatial and temporal patterns of synaptic input to SPNs produce spatially specific and stimulus-specific spine calcium responses in a biologically detailed computational model with sophisticated calcium dynamics. A sufficient number of excitatory inputs to a distal dendritic branch can cooperate to evoke supralinear spine calcium responses in the synaptically stimulated spines, whether the stimulated spines are clustered or dispersed along the distal portion of the branch. The resulting spine calcium responses exhibit specificity for synaptically stimulated spines, with an order of magnitude higher calcium influx than non-stimulated neighboring spines, and this spatial specificity is further enhanced by nearby GABAergic synaptic stimulation. Synaptic cooperativity exhibits dendritic-branch specificity, as synaptic inputs to one branch produce higher spine calcium responses than the same number of inputs distributed to multiple branches. Additionally, the calcium elevation in a proximal spine can be facilitated when the synaptic input to that spine occurs synchronous with or shortly following distally evoked plateau potentials, indicating potential interactions between distal and proximal synaptic input. Together, our results suggest that spine calcium elevation is a stimulus-specific signal which can differentiate between synaptically stimulated and non-stimulated spines. We predict that these distinct calcium responses will enable both input-specific LTP and heterosynaptic LTD, and that inhibition critically regulates heterosynaptic activity.In key ways, our results extend other experimental and modeling studies which have found that striatal spiny projection neurons exhibit plateau potentials in response to clustered excitation of neighboring spines on a distal dendritic branch . First, Our finding that coordinated synaptic inputs produce supralinear spine calcium elevation suggests a mechanism for ‘cooperative LTP’  in striatal SPNs. Although the induction of cooperative LTP by clustered synaptic input has not been demonstrated in SPNs, it has been observed in pyramidal neurons in cortex and hippocampus . In pyraOur finding that non-stimulated neighboring spines exhibit intermediate levels of calcium elevation suggests that these spines may undergo heterosynaptic plasticity (potentiation or depression) or metaplasticity. For instance, synaptic stimulation and induction of plasticity can induce metaplastic changes at nearby, non-stimulated spines in hippocampal pyramidal neurons . In contCalcium-dependent plasticity may also occur in the dendritic shaft. Dendritic spikes in pyramidal neurons can induce branch-specific potentiation of dendritic branch strength, via NMDAR-dependent regulation of dendritic potassium (Kv4.2) channels . Our resOur most novel result is that inhibition enhances spatial specificity. Although inhibition also attenuates the supralinear response to coordinated synaptic inputs, the reduction in non-stimulated spines is more significant. Our finding that inhibitory synaptic input located distally on the dendritic branch attenuates the supralinear response to coordinated excitatory synaptic inputs is consistent with recent studies in the striatum  and in cImportantly, our results are robust to parameter variations. The enhancement of spatial specificity by inhibition is most sensitive to NMDAR, CaR, and GABAR conductances, consistent with the NMDAR and CaR channels being the major sources of depolarization and calcium influx on synaptically stimulated and non-stimulated spines, respectively. The main finding that inhibition enhances spatial specificity was observed for all parameter variations (except for a 20% decrease in NMDAR conductance), although the amount that inhibition enhanced spatial specificity did depend on parameter values. Interestingly, both increases and decreases in NMDAR and CaR conductance reduced the ability for inhibition to increase spatial specificity. In the case of increased NMDAR or CaR conductance, greater depolarization would spread into non-stimulated spines, and the ability of the inhibitory current to counter the depolarization would be reduced. In the case of decreased NMDAR or CaR conductance, synapse-specificity is increased in the control (no inhibition) condition because weaker depolarization leads to significantly lower calcium influx to non-stimulated spines; thus, the ability of inhibition to further enhance spatial specificity is reduced. The sensitivity to NMDAR and CaR conductances is consistent with these channels being critical for plateau potential generation and duration in SPNs , and sugThe degree to which inhibition enhances spatial-specificity also is quite sensitive to GABAR conductance; however, the qualitative outcome is consistent for the entire range of GABAR conductances we evaluated. Therefore, the strength of inhibitory synapses may critically regulate spatial specificity and synaptic plasticity. We predict that calcium-dependent plasticity of inhibitory synapses, as has been observed in pyramidal neurons , may regThe computational modeling methods we employed assume that calcium dynamics in dendritic spines can be modeled deterministically with one-dimensional axial diffusion of calcium and mobile buffers. These assumptions may limit our ability to fully capture calcium dynamics in dendritic spines. However, the scope of the model, which includes the entire dendritic morphology with thousands of dendritic spines, precludes simulating stochastic reaction kinetics and diffusion in three-dimensions. Crucially, we verified that our conclusions did not depend on limitations of our modeling methodology. Specifically, our method may underestimate the calcium diffusion rate from narrow spine necks to the dendritic shaft . HoweverThe calcium modeling method of the GENESIS simulator also does not account for the local radius of curvature of the cell membrane, which may affect fluxes and reactions  at the membrane . HoweverTogether, our results have implications for striatal function and plasticity in vivo. With inputs likely to be spatiotemporally distributed, our results suggest that fewer than 10 spines per branch may produce supralinear spine calcium when a few hundred total synapses on the dendritic tree are stimulated, similar to estimates of the number of synaptic inputs driving striatal upstates . InhibitWe developed a biologically detailed multicompartment SPN model to investigate the effects of spatiotemporal patterns of synaptic input on calcium signaling. The model includes characterized morphology of SPN dendrites with explicitly modeled spines and ion channels that have been identified in SPNs. Uniquely, the model also includes sophisticated calcium dynamics consisting of calcium buffers, membrane pumps, and radial diffusion in dendrites and spines that enables us to predict how synaptic integration affects SPN calcium signaling.A biophysically detailed SPN model we previously published  was modi2 and 0.01 Farads/m2, respectively. Axial resistance was set to 1.25 ohm-m for all compartments except for spine neck compartments, which were set to 11.3 ohm-m to achieve a neck resistance of 500 MΩ, as estimated from experimental data  current equation to accurately account for the calcium driving potential. Calcium-dependent inactivation (CDI) was implemented for CaR, CaN, CaL1.2, and CaL1.3 channels . CaT chadifshell object in GENESIS  between difshells. The model included the endogenous mobile buffers calbindin and calmodulin , as well as an endogenous immobile buffer that was required to avoid unrealistic calcium elevations  and 0.1 % of the total AMPAR current. The AMPAR/NMDAR maximal conductance ratio was set to 1.0, and the conductances were set to achieve a unitary somatic PSP of ~2 mV, similar to the uncaging evoked EPSPs in NMDAR and AMPAR synaptic channels were included on the spine heads and contributed calcium to the outermost spine head A stimulation, GABAA synaptic channels were included on the dendritic shaft with a maximal conductance of 1.2 nS. GABAA kinetics were either fast, consistent with synapses from fast spiking interneurons, low-threshold spiking interneurons, or SPN collaterals ; Joshua Plotkin (Reviewer #3).Thank you for submitting your article "Inhibition enhances spine-specific calcium encoding of synaptic input patterns in a biologically constrained model" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.Summary:The manuscript by Dorman et al. describes a biologically grounded compartmental model of a striatal spiny projection neuron developed with the program GENESIS. The authors use the model to examine dendritic synaptic integration and calcium dynamics. The model incorporates channels responsible for the experimentally observed electrical behavior of the neurons. Numbers and locations of membrane channels and pumps have been "tuned" to reproduce observed electrical behavior, as well as observed calcium transients in activated spines. The model includes both excitatory and inhibitory synaptic "inputs".The authors verify that activation of a cluster of distal, but not proximal, dendritic spines produces a non-linear dendritic plateau potential, as observed experimentally. They then extend these findings to make testable predictions about synaptic cooperativity and heterosynaptic calcium dynamics in stimulated vs. unstimulated dendritic spines. They explore the effects of simultaneous vs. non-simultaneous coordinated stimulation of groups of distal spines on individual dendritic branches. They report that simultaneous coordinated synaptic stimulation evokes enhanced  elevation of calcium in stimulated spines and increases the specificity of the increase for stimulated vs. non-stimulated spines. This effect is specific to distal dendritic spines, suggesting that co-activation of spines on individual branches may lead to the most potent potentiation, and that distal branches may therefore act as relatively independent integrating units.They also explore the effect of coordinated distal synaptic stimulation onto different, neighboring dendritic branches, finding that the effects of coordinate activation are less pronounced when the inputs are on different branches. The data offer several new insights into these processes, such as the effects of spatial and temporal dispersion of stimulation on calcium summation and the contribution of NMDA receptors vs. VGCCs in mediating spine-specific supralinear calcium responses.The most novel finding, however, concerns the role of GABAergic inputs in shaping synaptic specificity during multi-synaptic stimulation. The authors show that single GABAergic synaptic inputs to distal dendrites can drastically increase the specificity of intra-spine calcium dynamics by increasing the difference between the sizes of calcium transients in stimulated vs. neighboring unstimulated spines. This has important implications for synaptic plasticity, and helps resolve a paradox of how synapse-specificity may be achieved under conditions where converging synaptic stimulation pushes an entire dendritic region into a depolarized plateau, a scenario that is now appreciated to represent a physiologically meaningful and important event.Essential revisions:eLife. However, there are major concerns that must be addressed before the manuscript would be suitable for publication. The concerns fall into two categories; the first is the writing style which is, at present, inadequate for the relatively general readership of eLife. The second concern derives from limitations of the model structure that the authors need to address.The work represents the kind of modeling that the reviewers would like to see published in Writing:eLife. The writing becomes less and less clear as it progresses through the presentation of figures. Here are a few examples:1) The manuscript is poorly written and must be thoroughly re-written in a less terse and more didactic style to be suitable for the relatively broad audience of The title of the section “Cooperative spine calcium exhibits dendritic branch independence” is vague. What is cooperative about the spine calcium? And what is independent about the branches? This ambiguous use of language is present throughout the writing in the paragraphs that follow. A better title would be something like "The supralinear calcium transient in spines that are activated simultaneously is largest when the co-activated spines are on the same dendritic branch."In the following paragraph, the authors begin using the term "inputs" to mean either synapses themselves or activated synapses. The authors should use the term activation whenever they refer to activated synapses. For example, "To investigate the effect of spatial dispersion of inputs, synaptic inputs were randomly distributed…". This sentence is ambiguous.It is not clear what the meaning is of "average interstimulus interval of 10 ms per branch with random temporal ordering". The methods do not describe exactly how this stimulation was structured. This leads to several questions about the stimulus itself:If the "temporal ordering" was random, were there still a certain percentage of spines that were activated simultaneously?2) The timing of the simulated FSI spike train relative to glutamatergic synaptic stimulation  should be clarified.3) The peak spine calcium data shown in Figure 6C is taken only from stimulated spines, correct? What length of dendrite was stimulated (with glutamatergic synapses) for each branch condition tested (1 vs. 2 branches), and was there a distance dependence of the simulated FSI train on the synaptic calcium responses ?4) In the experiments where distributed non-simultaneous synaptic stimulation was used to induce plateau potentials , is there a direction dependence (towards vs. away from soma) to stimulation, as shown for other neuron types? If so, does direction affect membrane potential, calcium dynamics or both?There are many instances of use of jargon and/or ambiguous wording, as well as sentences that are too terse to be clear. The manuscript needs a thorough editing to employ a better organized and more didactic style. One more example, "the duration of proximal spine calcium was prolonged when the proximal spine was stimulated prior to the distal cluster." The authors mean – "the calcium transients in the proximal spines were prolonged when proximal spines were stimulated prior to..." Note that calcium does not have a duration.eLife's more general readership.The section on the effects of GABA inputs was very difficult to read for all the above reasons. The authors seem to use GABA as a code for "activation of GABAergic inputs". This is an example of lab jargon. The sixth paragraph of the subsection “GABA attenuates stimulated spine calcium but enhances spatial specificity” needs to be re-organized and each individual issue should be discussed in a separate paragraph (for example fast vs. slow GABAergic receptor kinetics.) Briefly define the nature and meaning of a "confusion matrix" for In the Introduction, and throughout the Results section, the work should be better set into the context of previous work. This will not detract from the significance of the present work, rather it will enhance it. The supralinear response of a calcium transient in spines resulting from activation of NMDA receptors has long been studied in cortical and hippocampal synapses. Earlier hippocampal/cortical papers should be cited; for example, Schiller, Schiller and Clapham, 1998. A good early review is Sjöström and Nelson, 2002. A stochastic computer model of a hippocampal neuron that includes differential contributions to spine calcium from various sources is Bartol et al., 2015.The Introduction should contain a separate paragraph discussing the key differences between the anatomy and physiology of striatal spiny projection neurons and hippocampal and cortical projection neurons, including the observed synaptic plateau potentials, the up-state and down-state, and the observed differences between proximal and distal spines. In the Introduction and/or Discussion, a separate paragraph on the potential roles of the different sources of inhibitory inputs should be included. The present organization of the manuscript includes this background material interspersed throughout the Introduction, Results and Discussion, which becomes confusing.Model Structure:1) GENESIS  treat the problem of reaction/diffusion between compartments connected by bottlenecks (such as the spine neck connected to the dendritic shaft) as a 1D problem . It has been shown previously that this treatment greatly underestimates the diffusion flux across the mouth of the bottleneck . The underestimate is due to the formation of a 3D concentration gradient in the neighborhood of the mouth as the diffusing particles enter the larger space. This 3D diffusion gradient greatly increases the apparent flux area of the mouth. Only a full 3D method that captures this fine structure provides an accurate quantitative estimate of diffusion as it occurs in the space and time scales of real dendrites and spines. Because major conclusions of this study concern fluxes and exchange of calcium among clusters of spines on the dendrite, getting the diffusion rate right may be of critical importance to the conclusions. The authors should discuss this aspect of the model explicitly and, at the very least, include information about the sensitivity of the conclusion of the model to the diffusion rate of calcium out of spines into the dendrite. For example, if the diffusion rate were faster, as described in the Stiles paper, would the tuning of channel numbers have to be adjusted to reproduce experimental data? And would the major conclusions of the study regarding size and specificity of calcium fluxes in spines still hold?2) In computational science and numerical methods, the choice of temporal and spatial discretization of a PDE model is critical to achieve physically accurate results. For this reason, it is customary to validate a model by a test of convergence at ever finer space and time scales and through cross-validation with other simulation methods to demonstrate a robust solution. The authors should test the validity of their model using one or more of these techniques.3) The boundary conditions in PDE models of reaction/diffusion are also a critical factor to get right. It is very important to account for the localradius of curvature at the boundary in the diffusion and flux terms at the boundary. It is not clear that the PDEs employed in the difshell module of GENESIS account for this curvature. See equation 3 of Rangamani et al., 2013. This could have a significant impact on the inward Ca flux and outward pump fluxes.4) After addressing points 1-3 the calcium dynamics in the spines and dendrite may very well be different and will require the authors to re-tune the tunable parameters to compensate and restore a good fit to the experimental observations. It is unclear whether the authors' conclusions will hold up or be weakened. Essential revisionsThe work represents the kind of modeling that the reviewers would like to see published in eLife. However, there are major concerns that must be addressed before the manuscript would be suitable for publication. The concerns fall into two categories; the first is the writing style which is, at present, inadequate for the relatively general readership of eLife. The second concern derives from limitations of the model structure that the authors need to address.Writing:1) The manuscript is poorly written and must be thoroughly re-written in a less terse and more didactic style to be suitable for the relatively broad audience of eLife. The writing becomes less and less clear as it progresses through the presentation of figures.We have thoroughly revised the manuscript in a more didactic style. We addressed each of the specific concerns raised in the review detailed below, and we also revised the entire manuscript to make it clearer throughout to address the broader concerns about the writing style. We solicited feedback from new PhD students in the lab and lay people to ensure that the manuscript is accessible to a broad audience.The title of the section “Cooperative spine calcium exhibits dendritic branch independence” is vague. What is cooperative about the spine calcium? And what is independent about the branches? This ambiguous use of language is present throughout the writing in the paragraphs that follow. A better title would be something like "The supralinear calcium transient in spines that are activated simultaneously is largest when the co-activated spines are on the same dendritic branch."We have revised the section title similar to that recommended, i.e. “Synaptic cooperativity is strongest for synaptic inputs located on the same dendritic branch”. We eliminated the phrase “cooperative spine calcium” and other jargon from the entire manuscript.In the following paragraph, the authors begin using the term "inputs" to mean either synapses themselves or activated synapses. The authors should use the term activation whenever they refer to activated synapses. For example, "To investigate the effect of spatial dispersion of inputs, synaptic inputs were randomly distributed…". This sentence is ambiguous.We have revised our use of the term “inputs” to only mean stimulated synapses throughout the manuscript , and we use the term “synapses” without “inputs” to refer to any synapses themselves throughout the manuscript.It is not clear what the meaning is of "average interstimulus interval of 10 ms per branch with random temporal ordering". The methods do not describe exactly how this stimulation was structured. This leads to several questions about the stimulus itself.We have clarified the phrase in this paragraph, which now states “we used both simultaneous synaptic inputs and temporal dispersion, created by using random, exponentially distributed intervals. Simulations used average interstimulus intervals (ISIs) of 2.5, 5, or 10 ms, between synaptic inputs on each branch  . Specifying the ISI per branch has the advantage that the total duration of synaptic stimulation is independent of the number of branches.” We have also added a more detailed description of the temporal pattern in the Materials and methods .If the "temporal ordering" was random, were there still a certain percentage of spines that were activated simultaneously?Interstimulus intervals were randomly selected from an exponential distribution with the specified mean value. The minimum value was unconstrained, so it was possible for some intervals to be near zero. We have clarified this in the Materials and methods . Based on the exponential distribution, for an ISI of 5 ms, 5.6% of values are expected to be less than 0.3 ms, and for an ISI of 2.5 ms, 10.6% of values are expected to be less than 0.3 ms.2) The timing of the simulated FSI spike train relative to glutamatergic synaptic stimulation  should be clarified.We have clarified the figure caption and the description in the Results section to specify that “The onset of the FSI input train and the glutamatergic stimulation was simultaneous.”3) The peak spine calcium data shown in Figure 6C is taken only from stimulated spines, correct? What length of dendrite was stimulated (with glutamatergic synapses) for each branch condition tested (1 vs. 2 branches), and was there a distance dependence of the simulated FSI train on the synaptic calcium responses ?The referee is correct that peak spine calcium is shown only for stimulated spines in Figure 6C. Stimulated glutamatergic synapses were distributed over the entire dendritic branch . We have re-analyzed our results to determine whether the synapses that were facilitated are predominantly proximal or distal. We have added these results as Figure 6—figure supplement 1, and we added a description of these results in the Results section (see the aforementioned paragraph). This analysis revealed that the more distally located spines exhibited facilitated spine calcium responses , indicating that the depolarizing caused by the FSI train  propagates to the distal spines enough to facilitate calcium influx.4) In the experiments where distributed non-simultaneous synaptic stimulation was used to induce plateau potentials , is there a direction dependence (towards vs. away from soma) to stimulation, as shown for other neuron types? If so, does direction affect membrane potential, calcium dynamics or both?The temporal order for non-simultaneous synaptic stimulation was random and did not follow a spatial or distance-dependent rule, as we intended to simulate more in vivo like conditions for the simulations with spatiotemporally distributed inputs. Further, Plotkin et al. showed experimentally that there was no direction dependence of the somatic plateau potential when glutamatergic stimulation was applied in a distal-to-proximal or proximal-to-distal direction with 2 ms interstimulus intervals ; thus, we did not investigate whether our model exhibited a direction dependence. We have revised the description of these simulations in the Results section to clarify that the spatiotemporally distributed inputs were applied without a spatial pattern , and also in the Materials and methods .There are many instances of use of jargon and/or ambiguous wording, as well as sentences that are too terse to be clear. The manuscript needs a thorough editing to employ a better organized and more didactic style. One more example, "the duration of proximal spine calcium was prolonged when the proximal spine was stimulated prior to the distal cluster." The authors mean – "the calcium transients in the proximal spines were prolonged when proximal spines were stimulated prior to…" Note that calcium does not have a duration.We have thoroughly edited the manuscript throughout to consistently refer to “calcium elevation”, “calcium response”, or “calcium transients”, rather than the shorthand, ambiguously used “calcium”. We have specifically revised the sentence the reviewer gave as an example to state: “the duration of the calcium transient in the proximal spine was prolonged when the proximal spine was stimulated prior to the distal cluster”.The section on the effects of GABA inputs was very difficult to read for all the above reasons. The authors seem to use GABA as a code for "activation of GABAergic inputs". This is an example of lab jargon. The sixth paragraph of the subsection “GABA attenuates stimulated spine calcium but enhances spatial specificity” needs to be re-organized and each individual issue should be discussed in a separate paragraph (for example fast vs. slow GABAergic receptor kinetics.)We have revised our use of “GABA” to use “inhibition”, “GABAergic”, or “stimulation of GABAergic synapses” consistently throughout. We extensively revised the section on inhibition, including breaking it into 2 distinct sections: “Inhibition attenuates calcium elevation in stimulated spines”, and “Inhibition enhances stimulus-specificity of spine calcium transients”. However, we elected not to put fast vs. slow GABAergic receptor kinetics into separate paragraphs, as these results were qualitatively similar and only a single sentence is needed to state the results using fast GABAergic receptor kinetics once the results with slow GABAergic receptor kinetics are explained. Nonetheless, we revised our description of these results to make them clearer, and we maintained parallel sentence structure in descriptions of the fast and slow kinetics in each of the separate paragraphs on the timing or the location of GABAergic inputs .Briefly define the nature and meaning of a "confusion matrix" for eLife's more general readership.We have added a definition and description of the confusion matrix in the Results .In the Introduction, and throughout the Results section, the work should be better set into the context of previous work. This will not detract from the significance of the present work, rather it will enhance it. The supralinear response of a calcium transient in spines resulting from activation of NMDA receptors has long been studied in cortical and hippocampal synapses. Earlier hippocampal/cortical papers should be cited; for example, Schiller, Schiller and Clapham, 1998. A good early review is Sjöström and Nelson, 2002. A stochastic computer model of a hippocampal neuron that includes differential contributions to spine calcium from various sources is Bartol et al., 2015.The Introduction, Results, and Discussion has been extensively revised to include greater context of previous work. We reordered the Introduction to provide better flow and to better connect our work with the literature. We have included the suggested references in our paragraphs in the Introduction on non-linear forms of synaptic integration (second paragraph)and on supralinear plateau potentials producing elevated dendritic calcium concentration(fourth paragraph).In addition,we further discuss Bartol et al., 2015 in the Results and Discussion, as we found this paper specifically insightful for its presentation of calcium fates in dendritic spines . Thus, we performed an additional analysis and added a supplementary figure to our manuscript  with a similar presentation of calcium fates, for comparison to Bartol et al.The Introduction should contain a separate paragraph discussing the key differences between the anatomy and physiology of striatal spiny projection neurons and hippocampal and cortical projection neurons, including the observed synaptic plateau potentials, the up-state and down-state, and the observed differences between proximal and distal spines. In the Introduction and/or Discussion, a separate paragraph on the potential roles of the different sources of inhibitory inputs should be included. The present organization of the manuscript includes this background material interspersed throughout the Introduction, Results and Discussion, which becomes confusing.We have added a paragraph to the Introduction on key differences between striatal spiny projection neurons and pyramidal neurons (sixth paragraph), and a paragraph on the roles of inhibitory sources in the striatum (seventh paragraph). We have also extended comparisons to published work from pyramidal neurons in the Discussion (e.g. third paragraph).Model Structure:1) […] The underestimate is due to the formation of a 3D concentration gradient in the neighborhood of the mouth as the diffusing particles enter the larger space. This 3D diffusion gradient greatly increases the apparent flux area of the mouth. Only a full 3D method that captures this fine structure provides an accurate quantitative estimate of diffusion as it occurs in the space and time scales of real dendrites and spines. Because major conclusions of this study concern fluxes and exchange of calcium among clusters of spines on the dendrite, getting the diffusion rate right may be of critical importance to the conclusions. The authors should discuss this aspect of the model explicitly and, at the very least, include information about the sensitivity of the conclusion of the model to the diffusion rate of calcium out of spines into the dendrite. For example, if the diffusion rate were faster, as described in the Stiles paper, would the tuning of channel numbers have to be adjusted to reproduce experimental data? And would the major conclusions of the study regarding size and specificity of calcium fluxes in spines still hold?We are grateful for the reviewers’ comments addressing the model structure. We acknowledge that the one-dimensional approximation for diffusion and reaction is an approximation that should be more fully explored. The scope of our model, which includes the entire dendritic morphology and explicitly includes 3,280 dendritic spines, precludes a full 3D representation of reaction and diffusion. However, it is critical that our conclusions do not depend on the limitation of simulating calcium dynamics with a 1D approximation. To address the sensitivity of our conclusions that spine calcium transients exhibit stimulus-specificity and that inhibition enhances this specificity to the calcium diffusion parameters, we performed several simulations addressed here and in response to the subsequent specific items of concerns raised by the reviewers.First, we conducted additional sensitivity analysis simulations while varying the calcium diffusion rate from -50% to +100%  and observed no qualitative change in the outcome of our main result. We have added a description in the Results explaining our analysis of model robustness and sensitivity to diffusion parameters  and added paragraphs in the Discussion (ninth and tenth paragraphs) on the limitations of modeling 1D, deterministic calcium diffusion and reactions. Similar to what we showed with our initial sensitivity analysis  and our analysis of mechanisms underlying synapse-specific calcium transients , these additional results confirm that the specificity of spine calcium responses most strongly depends on distinct sources of calcium influx, and that diffusion of calcium only has a small effect.To further explore diffusion rate between the neck and dendritic shaft (or spine head), we modified the GENESIS source code to replace the default coupling coefficient for the shared surface area, which was the smaller of the two surface areas, with the geometric average of the two surface areas, which facilitates diffusion from the spine neck to the dendrite  This result has been included in the additional sensitivity analysis figure , showing no qualitative effect on the main result.2) In computational science and numerical methods, the choice of temporal and spatial discretization of a PDE model is critical to achieve physically accurate results. For this reason, it is customary to validate a model by a test of convergence at ever finer space and time scales and through cross-validation with other simulation methods to demonstrate a robust solution. The authors should test the validity of their model using one or more of these techniques.We have addressed the concern about temporal and spatial discretization by simulating the model with finer temporal and spatial scales. We decreased the simulation time step from 10 to 1 microsecond; we decreased the voltage compartment length in tertiary dendrites from 3 microns to 1 micron; and we increased the number of diffusion shells in the dendritic shafts, spine necks, and spine heads. We verified that our discretization of diffusion met stability requirements given by the equation D∆t(∆x)2≤12.This finer discretization had a trivial effect on the outcome of membrane potential in the soma or a dendritic spine and spine calcium transients in stimulated or non-stimulated spines. Finer discretization did not qualitatively change the main result that inhibition enhances spatial specificity of spine calcium elevation .3) The boundary conditions in PDE models of reaction/diffusion are also a critical factor to get right. It is very important to account for the localradius of curvature at the boundary in the diffusion and flux terms at the boundary. It is not clear that the PDEs employed in the difshell module of GENESIS account for this curvature. See equation 3 of Rangamani et al., 2013. This could have a significant impact on the inward Ca flux and outward pump fluxes.It is true that the difshell object in GENESIS does not account for local radius of curvature, but rather approximates each discretized calcium shell as a well-mixed volume, and the fluxes at the membrane are approximated using the total difshell membrane surface area and calcium concentration in the submembrane volume. While the scope of our model precludes simulating calcium dynamics at the same scale as Rangamani et al., 2013, we have assessed the sensitivity of our results to inward calcium flux and outward pump flux, shown by Rangamani et al. to be influenced by local curvature. We performed simulations that varied inward calcium flux through calcium permeable channels (while not varying the contribution of these channels to membrane depolarization) and calcium pump density from -50% to +100%. These results, which have been added to the new sensitivity analysis figure  indicate that our main results are not qualitatively affected by the specific membrane calcium fluxes. Indeed, although the magnitudes of calcium transients depend strongly on these parameters, the role of inhibition in enhancing spine-specificity does not depend strongly on the absolute magnitudes of calcium fluxes. With as much as a 50% reduction in calcium influx, inhibition still enhanced spatial specificity, though the degree to which inhibition did so was reduced.Additionally, to further address the limitations of the 1D approximation of calcium dynamics in our model, we have compared the fate of calcium influx into a spine in our model during a single synaptic stimulation  with a published computational model incorporating 3D, stochastic calcium reaction-diffusion in reconstructed dendritic spines  . We show the fraction of buffered, free, diffused, and pumped calcium in response to a single synaptic stimulation , which is similar to Figure 9 in Bartol et al., 2015. We have addressed the limitations regarding calcium influx and efflux (and their dependence on membrane curvature) in the Discussion (tenth paragraph).4) After addressing points 1-3 the calcium dynamics in the spines and dendrite may very well be different and will require the authors to re-tune the tunable parameters to compensate and restore a good fit to the experimental observations. It is unclear whether the authors' conclusions will hold up or be weakened.As our main results were robust to the additional simulations we performed , we concluded that retuning the model was not necessary.


Puberty is initiated by hormonal changes in the adolescent body that trigger physical and behavioral changes to reach adult maturation. As these changes occur, some adolescents experience concerning pubertal symptoms that are associated with dysfunction of the autonomic nervous system (ANS). Vasovagal syncope (VVS) and Postural Orthostatic Tachycardia Syndrome (POTS) are common disorders of the ANS associated with puberty that are related to orthostatic intolerance and share similar symptoms. Compared to young males, young females have decreased orthostatic tolerance and a higher incidence of VVS and POTS. As puberty is linked to changes in specific sex and non-sex hormones, and hormonal therapy sometimes improves orthostatic symptoms in female VVS patients, it is possible that pubertal hormones play a role in the increased susceptibility of young females to autonomic dysfunction. The purpose of this paper is to review the key hormonal changes associated with female puberty, their effects on the ANS, and their potential role in predisposing some adolescent females to cardiovascular autonomic dysfunctions such as VVS and POTS. Increases in pubertal hormones such as estrogen, thyroid hormones, growth hormone, insulin, and insulin-like growth factor-1 promote vasodilatation and decrease blood volume. This may be exacerbated by higher levels of progesterone, which suppresses catecholamine secretion and sympathetic outflow. Abnormal heart rate increases in POTS patients may be exacerbated by pubertal increases in leptin, insulin, and thyroid hormones acting to increase sympathetic nervous system activity and/or catecholamine levels. Given the coincidental timing of female pubertal hormone surges and adolescent onset of VVS and POTS in young women, coupled with the known roles of these hormones in modulating cardiovascular homeostasis, it is likely that female pubertal hormones play a role in predisposing females to VVS and POTS during puberty. Further research is necessary to confirm the effects of female pubertal hormones on autonomic function, and their role in pubertal autonomic disorders such as VVS and POTS, in order to inform the treatment and management of these debilitating disorders. Puberty is a period of adolescence in which a child undergoes rapid changes that affect physical and mental functioning in order to reach adult maturation. During this time many adolescents experience substantial fatigue, mood swings, and stress . These sSyncope and presyncope are common across the lifespan, but have a particularly high incidence in adolescents, with a peak age of onset during puberty at age ∼10–15 years ; approxiSyncope has many causes, including structural heart disease, cardiac arrhythmia, and impaired orthostatic cardiovascular control . Here weThe hormonal factors that initiate the onset and maintenance of puberty must be considered as possible culprits in the associated increased susceptibility to disorders of orthostatic intolerance, considering the timing of increased incidence of POTS and VVS with puberty . The iniFemales are known to have lower orthostatic tolerance compared to males , with a Orthostasis is a common trigger for VVS and POTS because when a person is upright gravitational forces decrease arterial pressures in regions above the level of the heart, while simultaneously increasing lower body venous pooling and capillary filtration, reducing venous return . If compOrthostatic reductions in arterial pressure are sensed primarily by baroreceptors located in the aortic arch, coronary arteries, and carotid sinus . The carUltimately, the cause of orthostatic presyncope or syncope is a failure of normal cardiovascular autonomic responses. However, different patterns of responses occur representing distinct autonomic syndromes, and this complicates their diagnosis and treatment. In POTS the primary problem is excessive orthostatic tachycardia, whereas in VVS it is impaired vasoconstriction and sudden hypotension, with or without reflex bradycardia or asystole . These aPostural Orthostatic Tachycardia Syndrome is defined as “the development of orthostatic symptoms associated with a HR increment ≥30 bpm (beats per minute) [≥40 bpm in children ], usuallPostural Orthostatic Tachycardia Syndrome includes at least four subtypes: hyperadrenergic POTS with excessive sympathetic discharge; hypovolemic POTS (with compensatory tachycardia); neuropathic POTS with impaired vasoconstriction and compensatory tachycardia; and, rarely, noradrenaline transporter deficiency with synaptic noradrenaline accumulation . Hemodynper se but rather to other competing vasodilatory influences at that time  act as a potent cerebral vasodilator, increasing cerebral blood flow  or follicle stimulating hormone (FSH) secretion and so prevents ovulation . NumerouThere may be a role for nutritional status and leptin in initiating puberty. Puberty starts earlier in overweight girls, and menstruation ceases with severe weight loss . AdiposiMelatonin secretion from the pineal gland also seems to regulate pubertal onset. Melatonin release occurs during sleep and darkness, with higher secretion during the winter when there are reduced daylight hours . The humMany of these key hormonal cues thought to be involved in the initiation of puberty also continue to be involved as puberty progresses, largely through their role in influencing the HPG axis.Once puberty is initiated and the HPG axis is activated, GnRH is released from the hypothalamus , with peIncreased activity of the gonads stimulated by LH and FSH during puberty results in an associated increased production of estrogen. During puberty, estrogen levels initially mirror LH and FSH changes, with the lowest levels in prepubertal girls at stage I . HoweverEstrogen acts to acutely regulate vasomotor tone through endothelium-dependent and independent mechanisms . E2 direEstradiol may also play a key role in regulating central nervous system factors that modulate adolescent behavior. For example, E2 may have the ability to modulate dopamine neurotransmission [dopaminergic neurons express estrogen receptors and mRNA ], contriIncreases in E2 have also been shown to increase serotonin concentrations by increasing the rate-limiting step in serotonin synthesis, as well as increasing the time that serotonin remains in the synapse and interstitial space . The latProgesterone secretion generally occurs in conjunction with E2, as it is regulated by gonadotropins and secreted by the ovaries and the placenta . It bindThe effects of progesterone in the absence of estrogen indicate that it promotes vasodilatation, blunts sympathetic outflow and increases plasma volume . ProgestETCO2 levels are reduced during times of high progesterone levels. For example, ventilation is increased during the luteal phase compared to the follicular phase of the menstrual cycle  increases substantially during the growth spurt of adolescence. It is secreted by the anterior pituitary gland in response to stimulation by GH releasing hormone from the hypothalamus . GH leveGrowth hormone acts as a vasodilator through activation of an endothelium-dependent component involving the NO pathway  to improInsulin-like growth factor-1 (IGF-1) production follows similar patterns to GH secretion during puberty; it is stimulated by GH in the liver and further enhanced by estrogen and thyroid hormones . In femaInsulin-like growth factor-1 induces vasodilation by enhancing NO and potassium channel activity, both of which reduce calcium release into vascular smooth muscle, blunting vasoconstriction . IGF-1 iDuring female puberty insulin levels generally coincide with changes in IGF-1 levels . FastingPuberty is associated with a marked decrease in insulin sensitivity, on par with that seen during pregnancy. In otherwise healthy youth, insulin sensitivity reaches a nadir in mid-puberty (stage III) that recovers by stage V . In patiIn children with type 1 diabetes, profound insulin resistance associated with puberty is well documented, although effects on the ANS in these children are not well studied. In one study evaluating 73 diabetic children, abnormalities in heart rate variability (a marker of autonomic dysfunction) were correlated with poor glycemic control in pubertal children. This relationship was not seen in younger children .Insulin exhibits both central and peripheral effects on the ANS – insulin both promotes vasodilatation and prevents vasoconstriction, while also having the ability to stimulate sympathetic activity. Insulin diminishes arterial stiffness  and actsThe thyroid gland produces triiodothyronine (T3) and thyroxine (T4), both of which are stimulated by thyroid-stimulating hormone from the anterior pituitary gland secondary to release of thyrotropin-releasing hormone from the hypothalamus . The relHigher levels of thyroid hormones increase metabolism and heat production stimulating hypothalamic reflex responses . These hBaseline cortisol levels increase during puberty, peaking at stage IV/V in females . CortisoAcute increases in cortisol levels blunt autonomic reactivity by suppressing the early effects of catecholamines in the brain , with suLeptin levels increase with the onset of puberty, but remain fairly steady following this initial rise until a late surge starting at stage IV in females . Leptin Leptin activates the sympathetic nervous system through hypothalamic mechanisms that are mediated by neuropeptide systems, including the melanocortin system and corticotropin-releasing hormone . With inIn the early stages of female puberty (I and II) melatonin secretion significantly decreases, with further successive decreases in the later stages . MelatonMelatonin interferes with E2 signaling by impairing estrogen receptor pathways via specific inhibition of E2-induced estrogen receptor alpha (ERα) mediated transcription of both estrogen response element and activator protein 1 containing promoters . By reduIncreases in kisspeptin levels and decreases in GnIH levels are thought to contribute to the initiation of puberty . HoweverThere are numerous factors known to increase susceptibility to syncope. One key contributor is excessive vasodilatation and/or impaired vasoconstrictor responses, often associated with hypotension and blunted sympathetic outflow . In addiThe implications for these hormones as possible contributors to VVS and POTS can be considered based on the impact each has on cardiovascular control , and theThe effects of these hormones on the ANS may be more prominent in some individuals, leading to a greater predisposition to POTS or VVS. As cortisol levels have been shown to increase during vasovagal reactions in patients with VVS , peak leCentral hyperadrenergic POTS and the abnormal heart rate increases in POTS patients could be exacerbated by hormones involved in increasing sympathetic activity and elevating norepinephrine levels . Both inWhile it is certainly not possible to imply causality between these pubertal hormone changes and disorders of orthostatic tolerance in adolescents, the coincidental timing of these profound hormonal changes – many of which have marked cardiovascular effects - and the timing of onset of VVS and POTS, together with the observation that many youth “grow out” of their symptoms , is suggHormone changes during puberty have the potential to impact cardiovascular autonomic control and as such may play a role in predisposing adolescent females to autonomic dysfunction, including disorders of orthostatic intolerance such as POTS and VVS. The peak incidence of VVS and POTS in young women occurs at approximately 10–15 years of age, a time where many hormones involved in puberty, capable of predisposing to disorders of orthostatic intolerance, are at peak levels. These pubertal hormones can act to promote vasodilatation, impair vasoconstriction, decrease plasma volume, promote hypocapnia and cerebral hypoperfusion, and contribute to excessive tachycardia. Additional research is necessary to examine the potential role that puberty, and in particular the hormonal changes that accompany it, may have in predisposing young females to orthostatic intolerance and autonomic dysfunction during their pubertal years.KC, NH, BH, and VC wrote the manuscript. RR, KA, and SS provided critical analysis, insight, editing, and review of intellectual content.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Dear Editor.Recently, we have read with tremendous interest the article published by Prof. Gattinoni et al. , which i2/FiO2 between 124 and 150 had a mortality rate of 35%. Moreover, this favorable cardiovascular effect could explain the clinical benefits of prone positioning in terms of mortality reduction, thanks to the decrease in afterload and unloading of the RV [Obviously, veno-venous extracorporeal membrane oxygenation (VV ECMO) indications are related to respiratory syndromes, and traditionally, its indication criteria were limited to gas exchange and respiratory mechanics. However, we consider that VV ECMO indications should not be limited to these. Cardiopulmonary interactions during severe acute respiratory distress syndrome (ARDS), perhaps, plays a paramount role in the pathophysiologic derangements which leads to organic failure with its obvious consequences, from the increase in right ventricle (RV) afterload secondary to hypoxic pulmonary vasoconstriction  to the iWe do not deny the clinical importance of hypoxemia in the pathophysiological context of ARDS as a VV ECMO indication, but certainly a more realistic approach should look beyond the classical criteria to start ECMO therapy and take into account the heart-lung interactions its effects and implications in the prognosis of patients with acute respiratory failure. Also, we understand that more data and scientific evidence is needed to support such clinical approach, but perhaps it is time to start raising it and consider it as a potential indication in future clinical studies.