Assessing exogenous carbohydrate intake needed to optimize human endurance performance across sex: insights from modeling runners pursuing a sub-2-h marathon.

Carbohydrate (CHO) availability sustains high metabolic demands during prolonged exercise. The adequacy of current CHO intake recommendations, 30-90 g·h-1 dependent on CHO mixture and tolerability, to support elite marathon performance is unclear. We sought to scrutinize the current upper limit recommendation for exogenous CHO intake to support modeled sub-2-h marathon (S2M) attempts across elite male and female runners. Male and female runners (n = 120 each) were modeled from published literature with reference characteristics necessary to complete a S2M (e.g., body mass and running economy). Completion of a S2M was considered across a range of respiratory exchange rates, with maximal starting skeletal muscle and liver glycogen content predicted for elite male and female runners. Modeled exogenous CHO bioavailability needed for male and female runners were 93 ± 26 and 108 ± 22 g·h-1, respectively (P < 0.0001, d = 0.61). Without exogenous CHO, males were modeled to deplete glycogen in 84 ± 7 min, females in 71 ± 5 min (P < 0.0001, d = 2.21) despite higher estimated CHO oxidation rates in males (5.1 ± 0.5 g·h-1) than females (4.4 ± 0.5 g·h-1; P < 0.0001, d = 1.47). Exogenous CHO intakes ≤ 90 g·h-1 are insufficient for 65% of modeled runners attempting a S2M. Current recommendations to support marathon performance appear inadequate for elite marathon runners but may be more suitable for male runners in pursuit of a S2M (56 of 120) than female runners (28 of 120).NEW & NOTEWORTHY This study scrutinizes the upper limit of exogenous carbohydrate (CHO) recommendations for elite male and female marathoners by modeling sex-specific needs across an extreme metabolic challenge lasting ∼2 h, a sub-2-h marathon. Contemporary nutritional guidelines to optimize marathon performance appear inadequate for most elite marathon runners but appear more appropriate for males over their female counterparts. Future research examining possible benefits of exogenous CHO intakes > 90 g·h-1 should prioritize female athlete study inclusion.

Implications of capacity-limited, generative models for human vision.

Although discriminative deep neural networks are currently dominant in cognitive modeling, we suggest that capacity-limited, generative models are a promising avenue for future work. Generative models tend to learn both local and global features of stimuli and, when properly constrained, can learn componential representations and response biases found in people's behaviors.

A practical perspective on how to develop, implement, execute, and reproduce high-resolution respirometry experiments: The physiologist's guide to an Oroboros O2k.

The development of high-resolution respirometry (HRR) has greatly expanded the analytical scope to study mitochondrial respiratory control relative to specific tissue/cell types across various metabolic states. Specifically, the Oroboros Oxygraph 2000 (O2k) is a common tool for measuring rates of mitochondrial respiration and is the focus of this perspective. The O2k platform is amenable for answering numerous bioenergetic questions. However, inherent variability with HRR-derived data, both within and amongst users, can impede progress in bioenergetics research. Therefore, we advocate for several vital considerations when planning and conducting O2k experiments to ultimately enhance transparency and reproducibility across laboratories. In this perspective, we offer guidance for best practices of mitochondrial preparation, protocol selection, and measures to increase reproducibility. The goal of this perspective is to propagate the use of the O2k, enhance reliability and validity for both new and experienced O2k users, and provide a reference for peer reviewers.

Rapid runtime learning by curating small datasets of high-quality items obtained from memory.

We propose the "runtime learning" hypothesis which states that people quickly learn to perform unfamiliar tasks as the tasks arise by using task-relevant instances of concepts stored in memory during mental training. To make learning rapid, the hypothesis claims that only a few class instances are used, but these instances are especially valuable for training. The paper motivates the hypothesis by describing related ideas from the cognitive science and machine learning literatures. Using computer simulation, we show that deep neural networks (DNNs) can learn effectively from small, curated training sets, and that valuable training items tend to lie toward the centers of data item clusters in an abstract feature space. In a series of three behavioral experiments, we show that people can also learn effectively from small, curated training sets. Critically, we find that participant reaction times and fitted drift rates are best accounted for by the confidences of DNNs trained on small datasets of highly valuable items. We conclude that the runtime learning hypothesis is a novel conjecture about the relationship between learning and memory with the potential for explaining a wide variety of cognitive phenomena.

Erythropoietin receptor regulates tumor mitochondrial biogenesis through iNOS and pAKT.

Erythropoietin receptor (EPOR) is widely expressed in healthy and malignant tissues. In certain malignancies, EPOR stimulates tumor growth. In healthy tissues, EPOR controls processes other than erythropoiesis, including mitochondrial metabolism. We hypothesized that EPOR also controls the mitochondrial metabolism in cancer cells. To test this hypothesis, we generated EPOR-knockdown cancer cells to grow tumor xenografts in mice and analyzed tumor cellular respiration via high-resolution respirometry. Furthermore, we analyzed cellular respiratory control, mitochondrial content, and regulators of mitochondrial biogenesis in vivo and in vitro in different cancer cell lines. Our results show that EPOR controls tumor growth and mitochondrial biogenesis in tumors by controlling the levels of both, pAKT and inducible NO synthase (iNOS). Furthermore, we observed that the expression of EPOR is associated with the expression of the mitochondrial marker VDAC1 in tissue arrays of lung cancer patients, suggesting that EPOR indeed helps to regulate mitochondrial biogenesis in tumors of cancer patients. Thus, our data imply that EPOR not only stimulates tumor growth but also regulates tumor metabolism and is a target for direct intervention against progression.

Conceptual knowledge shapes visual working memory for complex visual information.

Human visual working memory (VWM) is a memory store people use to maintain the visual features of objects and scenes. Although it is obvious that bottom-up information influences VWM, the extent to which top-down conceptual information influences VWM is largely unknown. We report an experiment in which groups of participants were trained in one of two different categories of geologic faults (left/right lateral, or normal/reverse faults), or received no category training. Following training, participants performed a visual change detection task in which category knowledge was irrelevant to the task. Participants were more likely to detect a change in geologic scenes when the changes crossed a trained categorical distinction (e.g., the left/right lateral fault boundary), compared to within-category changes. In addition, participants trained to distinguish left/right lateral faults were more likely to detect changes when the scenes were mirror images along the left/right dimension. Similarly, participants trained to distinguish normal/reverse faults were more likely to detect changes when scenes were mirror images along the normal/reverse dimension. Our results provide direct empirical evidence that conceptual knowledge influences VWM performance for complex visual information. An implication of our results is that cognitive scientists may need to reconceptualize VWM so that it is closer to "conceptual short-term memory".

Analogy-Related Information Can Be Accessed by Simple Addition and Subtraction of fMRI Activation Patterns, Without Participants Performing any Analogy Task.

Analogical reasoning, for example, inferring that teacher is to chalk as mechanic is to wrench, plays a fundamental role in human cognition. However, whether brain activity patterns of individual words are encoded in a way that could facilitate analogical reasoning is unclear. Recent advances in computational linguistics have shown that information about analogical problems can be accessed by simple addition and subtraction of word embeddings (e.g., wrench = mechanic + chalk - teacher). Critically, this property emerges in artificial neural networks that were not trained to produce analogies but instead were trained to produce general-purpose semantic representations. Here, we test whether such emergent property can be observed in representations in human brains, as well as in artificial neural networks. fMRI activation patterns were recorded while participants viewed isolated words but did not perform analogical reasoning tasks. Analogy relations were constructed from word pairs that were categorically or thematically related, and we tested whether the predicted fMRI pattern calculated with simple arithmetic was more correlated with the pattern of the target word than other words. We observed that the predicted fMRI patterns contain information about not only the identity of the target word but also its category and theme (e.g., teaching-related). In summary, this study demonstrated that information about analogy questions can be reliably accessed with the addition and subtraction of fMRI patterns, and that, similar to word embeddings, this property holds for task-general patterns elicited when participants were not explicitly told to perform analogical reasoning.

Semantic influence on visual working memory of object identity and location.

Does semantic information-in particular, regularities in category membership across objects-influence visual working memory (VWM) processing? We predict that the answer is "yes". Four experiments evaluating this prediction are reported. Experimental stimuli were images of real-world objects arranged in either one or two spatial clusters. On coherent trials, all objects belonging to a cluster also belonged to the same category. On incoherent trials, at least one cluster contained objects from different categories. Experiments using a change-detection paradigm (Experiments 1-3) and an experiment in which participants recalled the locations of objects in a scene (Experiment 4) yielded the same result: participants showed better memory performance on coherent trials than on incoherent trials. Taken as a whole, these experiments provide the best (perhaps only) data to date demonstrating that statistical regularities in semantic category membership improve VWM performance. Because a conventional perspective in cognitive science regards VWM as being sensitive solely to bottom-up visual properties of objects (e.g., shape, color, orientation), our results indicate that cognitive science may need to modify its conceptualization of VWM so that it is closer to "conceptual short-term memory", a short-term memory store representing current stimuli and their associated concepts (Potter, 1993, 2012).

Erythropoietin promotes hippocampal mitochondrial function and enhances cognition in mice.

Erythropoietin (EPO) improves neuronal mitochondrial function and cognition in adults after brain injury and in those afflicted by psychiatric disorders. However, the influence of EPO on mitochondria and cognition during development remains unexplored. We previously observed that EPO stimulates hippocampal-specific neuronal maturation and synaptogenesis early in postnatal development in mice. Here we show that EPO promotes mitochondrial respiration in developing postnatal hippocampus by increasing mitochondrial content and enhancing cellular respiratory potential. Ultrastructurally, mitochondria profiles and total vesicle content were greater in presynaptic axon terminals, suggesting that EPO enhances oxidative metabolism and synaptic transmission capabilities. Behavioural tests of hippocampus-dependent memory at early adulthood, showed that EPO improves spatial and short-term memory. Collectively, we identify a role for EPO in the murine postnatal hippocampus by promoting mitochondrial function throughout early postnatal development, which corresponds to enhanced cognition by early adulthood.

Optimal attentional allocation in the presence of capacity constraints in uncued and cued visual search.

The vision sciences literature contains a large diversity of experimental and theoretical approaches to the study of visual attention. We argue that this diversity arises, at least in part, from the field's inability to unify differing theoretical perspectives. In particular, the field has been hindered by a lack of a principled formal framework for simultaneously thinking about both optimal attentional processing and capacity-limited attentional processing, where capacity is limited in a general, task-independent manner. Here, we supply such a framework based on rate-distortion theory (RDT) and optimal lossy compression. Our approach defines Bayes-optimal performance when an upper limit on information processing rate is imposed. In this article, we compare Bayesian and RDT accounts in both uncued and cued visual search tasks. We start by highlighting a typical shortcoming of unlimited-capacity Bayesian models that is not shared by RDT models, namely, that they often overestimate task performance when information-processing demands are increased. Next, we reexamine data from two cued-search experiments that have previously been modeled as the result of unlimited-capacity Bayesian inference and demonstrate that they can just as easily be explained as the result of optimal lossy compression. To model cued visual search, we introduce the concept of a "conditional communication channel." This simple extension generalizes the lossy-compression framework such that it can, in principle, predict optimal attentional-shift behavior in any kind of perceptual task, even when inputs to the model are raw sensory data such as image pixels. To demonstrate this idea's viability, we compare our idealized model of cued search, which operates on a simplified abstraction of the stimulus, to a deep neural network version that performs approximately optimal lossy compression on the real (pixel-level) experimental stimuli.

Contextualizing the biological relevance of standardized high-resolution respirometry to assess mitochondrial function in permeabilized human skeletal muscle.

AIM: This study sought to provide a statistically robust reference for measures of mitochondrial function from standardized high-resolution respirometry with permeabilized human skeletal muscle (ex vivo), compare analogous values obtained via indirect calorimetry, arterial-venous O2 differences and 31 P magnetic resonance spectroscopy (in vivo) and attempt to resolve differences across complementary methodologies as necessary. METHODS: Data derived from 831 study participants across research published throughout March 2009 to November 2019 were amassed to examine the biological relevance of ex vivo assessments under standard conditions, ie physiological temperatures of 37°C and respiratory chamber oxygen concentrations of ~250 to 500 µmol/L. RESULTS: Standard ex vivo-derived measures are lower (Z ≥ 3.01, P ≤ .0258) en masse than corresponding in vivo-derived values. Correcting respiratory values to account for mitochondrial temperatures 10°C higher than skeletal muscle temperatures at maximal exercise (~50°C): (i) transforms data to resemble (Z ≤ 0.8, P > .9999) analogous yet context-specific in vivo measures, eg data collected during maximal 1-leg knee extension exercise; and (ii) supports the position that maximal skeletal muscle respiratory rates exceed (Z ≥ 13.2, P < .0001) those achieved during maximal whole-body exercise, e.g. maximal cycling efforts. CONCLUSION: This study outlines and demonstrates necessary considerations when actualizing the biological relevance of human skeletal muscle respiratory control, metabolic flexibility and bioenergetics from standard ex vivo-derived assessments using permeabilized human muscle. These findings detail how cross-procedural comparisons of human skeletal muscle mitochondrial function may be collectively scrutinized in their relationship to human health and lifespan.

High-intensity interval exercise reduces tolerance to a simulated haemorrhagic challenge in heat-stressed individuals.

NEW FINDINGS: What is the central question of this study? In heat-stressed individuals, does high-intensity interval exercise reduce tolerance to a simulated haemorrhagic challenge (lower body negative pressure, LBNP) relative to steady state exercise? What is the main finding and its importance? LBNP tolerance was lower in heat-stressed individuals following high-intensity interval exercise relative to steady state exercise. This was likely owing to the greater cardiovascular strain required to maintain arterial blood pressure prior to and early during LBNP following high-intensity interval exercise. These findings are of importance for individuals working in occupations in which combined heat stress and intense intermittent exercise are common and where the risk of haemorrhagic injury is increased. ABSTRACT: This study investigated whether tolerance to a simulated haemorrhagic challenge (lower body negative pressure, LBNP) was lower in heat-stressed individuals following high-intensity interval exercise relative to steady state exercise. Nine healthy participants completed two trials (Steady State and Interval). Participants cycled continuously at ∼38% (Steady State) or alternating between 10 and ∼88% (Interval) of the maximal power output whilst wearing a hot water perfused suit until core temperatures increased ∼1.4°C. Participants then underwent LBNP to pre-syncope. LBNP tolerance was quantified as cumulative stress index (CSI; mmHg min). Mean skin and core temperatures were elevated in both trials following exercise prior to LBNP (to 38.1 ± 0.6°C and 38.3 ± 0.2°C, respectively, both P < 0.001 relative to baseline) but not different between trials (both P > 0.05). In the Interval trial, heart rate was greater (122 ± 12 beats min-1 ) prior to LBNP, relative to the Steady State trial (107 ± 8 beats min-1 , P < 0.001) while mean arterial pressure was similarly reduced in both trials prior to LBNP (from baseline 89 ± 5 to 77 ± 7 mmHg; P = 0.001) and at pre-syncope (to 62 ± 9 mmHg, P < 0.001). CSI was lower in the Interval trial (280 ± 194 vs. 550 ± 234 mmHg min; P = 0.0085). In heat-stressed individuals, tolerance to a simulated haemorrhagic challenge is reduced following high-intensity interval exercise relative to steady state exercise.

Efficient data compression in perception and perceptual memory.

Efficient data compression is essential for capacity-limited systems, such as biological perception and perceptual memory. We hypothesize that the need for efficient compression shapes biological systems in many of the same ways that it shapes engineered systems. If true, then the tools that engineers use to analyze and design systems, namely rate-distortion theory (RDT), can profitably be used to understand human perception and memory. The first portion of this article discusses how three general principles for efficient data compression provide accounts for many important behavioral phenomena and experimental results. We also discuss how these principles are embodied in RDT. The second portion notes that exact RDT methods are computationally feasible only in low-dimensional stimulus spaces. To date, researchers have used deep neural networks to approximately implement RDT in high-dimensional spaces, but these implementations have been limited to tasks in which the sole goal is compression with respect to reconstruction error. Here, we introduce a new deep neural network architecture that approximately implements RDT. An important property of our architecture is that it is trained "end-to-end," operating on raw perceptual input (e.g., pixel values) rather than intermediate levels of abstraction, as is the case with most psychological models. The article's final portion conjectures on how efficient compression can occur in memory over time, thereby providing motivations for multiple memory systems operating at different time scales, and on how efficient compression may explain some attentional phenomena such as RTs in visual search. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The importance of constraints on constraints.

The "resource-rational" approach is ambitious and worthwhile. A shortcoming of the proposed approach is that it fails to constrain what counts as a constraint. As a result, constraints used in different cognitive domains often have nothing in common. We describe an alternative framework that satisfies many of the desiderata of the resource-rational approach, but in a more disciplined manner.

Improving biologic predictors of cycling endurance performance with near-infrared spectroscopy derived measures of skeletal muscle respiration: E pluribus unum.

The study aim was to compare the predictive validity of the often referenced traditional model of human endurance performance (i.e. oxygen consumption, VO2 , or power at maximal effort, fatigue threshold values, and indices of exercise efficiency) versus measures of skeletal muscle oxidative potential in relation to endurance cycling performance. We hypothesized that skeletal muscle oxidative potential would more completely explain endurance performance than the traditional model, which has never been collectively verified with cycling. Accordingly, we obtained nine measures of VO2 or power at maximal efforts, 20 measures reflective of various fatigue threshold values, 14 indices of cycling efficiency, and near-infrared spectroscopy-derived measures reflecting in vivo skeletal muscle oxidative potential. Forward regression modeling identified variable combinations that best explained 25-km time trial time-to-completion (TTC) across a group of trained male participants (n = 24). The time constant for skeletal muscle oxygen consumption recovery, a validated measure of maximal skeletal muscle respiration, explained 92.7% of TTC variance by itself (Adj R2  = .927, F = 294.2, SEE = 71.2, p < .001). Alternatively, the best complete traditional model of performance, including VO2max (L·min-1 ), %VO2max determined by the ventilatory equivalents method, and cycling economy at 50 W, only explained 76.2% of TTC variance (Adj R2  = .762, F = 25.6, SEE = 128.7, p < .001). These results confirm our hypothesis by demonstrating that maximal rates of skeletal muscle respiration more completely explain cycling endurance performance than even the best combination of traditional variables long postulated to predict human endurance performance.

Can machine learning account for human visual object shape similarity judgments?

We describe and analyze the performance of metric learning systems, including deep neural networks (DNNs), on a new dataset of human visual object shape similarity judgments of naturalistic, part-based objects known as "Fribbles". In contrast to previous studies which asked participants to judge similarity when objects or scenes were rendered from a single viewpoint, we rendered Fribbles from multiple viewpoints and asked participants to judge shape similarity in a viewpoint-invariant manner. Metrics trained using pixel-based or DNN-based representations fail to explain our experimental data, but a metric trained with a viewpoint-invariant, part-based representation produces a good fit. We also find that although neural networks can learn to extract the part-based representation-and therefore should be capable of learning to model our data-networks trained with a "triplet loss" function based on similarity judgments do not perform well. We analyze this failure, providing a mathematical description of the relationship between the metric learning objective function and the triplet loss function. The poor performance of neural networks appears to be due to the nonconvexity of the optimization problem in network weight space. We conclude that viewpoint insensitivity is a critical aspect of human visual shape perception, and that neural network and other machine learning methods will need to learn viewpoint-insensitive representations in order to account for people's visual object shape similarity judgments.

Can multisensory training aid visual learning? A computational investigation.

Although real-world environments are often multisensory, visual scientists typically study visual learning in unisensory environments containing visual signals only. Here, we use deep or artificial neural networks to address the question, Can multisensory training aid visual learning? We examine a network's internal representations of objects based on visual signals in two conditions: (a) when the network is initially trained with both visual and haptic signals, and (b) when it is initially trained with visual signals only. Our results demonstrate that a network trained in a visual-haptic environment (in which visual, but not haptic, signals are orientation-dependent) tends to learn visual representations containing useful abstractions, such as the categorical structure of objects, and also learns representations that are less sensitive to imaging parameters, such as viewpoint or orientation, that are irrelevant for object recognition or classification tasks. We conclude that researchers studying perceptual learning in vision-only contexts may be overestimating the difficulties associated with important perceptual learning problems. Although multisensory perception has its own challenges, perceptual learning can become easier when it is considered in a multisensory setting.

Adaptive allocation of human visual working memory capacity during statistical and categorical learning.

Human brains are finite, and thus have bounded capacity. An efficient strategy for a capacity-limited agent is to continuously adapt by dynamically reallocating capacity in a task-dependent manner. Here we study this strategy in the context of visual working memory (VWM). People use their VWM stores to remember visual information over seconds or minutes. However, their memory performances are often error-prone, presumably due to VWM capacity limits. We hypothesize that people attempt to be flexible and robust by strategically reallocating their limited VWM capacity based on two factors: (a) the statistical regularities (e.g., stimulus feature means and variances) of the to-be-remembered items, and (b) the requirements of the task that they are attempting to perform. The latter specifies, for example, which types of errors are costly versus irrelevant for task performance. These hypotheses are formalized within a normative computational modeling framework based on rate-distortion theory, an extension of conventional Bayesian approaches that uses information theory to study rate-limited (or capacity-limited) processes. Using images of plants that are naturalistic and precisely controlled, we carried out two sets of experiments. Experiment 1 found that when a stimulus dimension (the widths of plants' leaves) was assigned a distribution, subjects adapted their VWM performances based on this distribution. Experiment 2 found that when one stimulus dimension (e.g., leaf width) was relevant for distinguishing plant categories but another dimension (leaf angle) was irrelevant, subjects' responses in a memory task became relatively more sensitive to the relevant stimulus dimension. Together, these results illustrate the task-dependent robustness of VWM, thereby highlighting the dependence of memory on learning.

Supplemental Oxygen Does Not Influence Self-selected Work Rate at Moderate Altitude.

INTRODUCTION: It is well known that supplemental oxygen can increase aerobic power output during high-intensity and/or maximal efforts at moderate altitude, yet the effects on self-selected work rate during lower-intensity, submaximal exercise are unknown. We reasoned that if the degree of arterial oxygen saturation (SaO2) influences teleoanticipatory regulation of power output, supplemental oxygen given at moderate altitude would increase average power output during exercise performed at self-selected work rates corresponding to RPE 9 (very light) and 13 (somewhat hard). METHODS: Twenty-three subjects (17 males, 6 females) completed one familiarization [fraction of inspired O2 (FIO2) = 0.209] and two blinded, experimental trials (FIO2 = 0.209 and FIO2 = 0.267). In each trial, subjects self-regulated their work rate on a cycle ergometer to maintain RPE 9 for 5 min and RPE 13 for 10 min, before performing an incremental step test to exhaustion (25 W·min). Oxygen consumption (V˙O2) and SaO2 via pulse oximetry (SpO2) were continuously monitored. Subjects were asked to guess the experimental condition after each stage of the protocol. RESULTS: Supplemental oxygen increased SpO2 throughout exercise (~4%; P < 0.001) and was associated with greater peak power output (4% ± 4%; P < 0.001) and V˙O2 (5% ± 10%; P = 0.010) during the incremental test, but did not increase average power output selected during exercise at RPE 9 (P = 0.235) or 13 (P = 0.992). Subjects were unable to perceive the difference in FIO2 at any stage (P > 0.14). CONCLUSIONS: Small increases in inspired oxygen concentration at moderate altitude are imperceptible and do not appear to influence selection of submaximal work rates at RPE ≤ 13.

Small reductions in skin temperature after onset of a simulated hemorrhagic challenge improve tolerance in exercise heat-stressed individuals.

We investigated whether small reductions in skin temperature 60 s after the onset of a simulated hemorrhagic challenge would improve tolerance to lower body negative pressure (LBNP) after exercise heat stress. Eleven healthy subjects completed two trials (High and Reduced). Subjects cycled at ~55% maximal oxygen uptake wearing a warm water-perfused suit until core temperatures increased by ~1.2°C before lying supine and undergoing LBNP to presyncope. LBNP tolerance was quantified as cumulative stress index (CSI; product of each LBNP level multiplied by time; mmHg·min). Skin temperature was similarly elevated from baseline before LBNP and remained elevated 60 s after the onset of LBNP in both High (37.72 ± 0.52°C) and Reduced (37.95 ± 0.54°C) trials (both P < 0.0001). At 60%CSI skin temperature remained elevated in the High trial (37.51 ± 0.56°C) but was reduced to 34.97 ± 0.72°C by the water-perfused suit in the Reduced trial ( P < 0.0001 between trials). Cutaneous vascular conductance was not different between trials [High: 1.57 ± 0.43 vs. Reduced: 1.39 ± 0.38 arbitrary units (AU)/mmHg; P = 0.367] before LBNP but decreased to 0.67 ± 0.19 AU/mmHg at 60%CSI in the Reduced trial while remaining unchanged in the High trial ( P = 0.002 between trials). CSI was higher in the Reduced (695 ± 386 mmHg·min) relative to the High (441 ± 290 mmHg·min; P = 0.023) trial. Mean arterial pressure was not different between trials at presyncope (High: 62 ± 10 vs. Reduced: 62 ± 9 mmHg; P = 0.958). Small reductions in skin temperature after the onset of a simulated hemorrhagic challenge improve LBNP tolerance after exercise heat stress. This may have important implications regarding treatment of an exercise heat-stressed individual (e.g., soldier) who has experienced a hemorrhagic injury.