Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules.

Self-sustained neural activity maintained through local recurrent connections is of fundamental importance to cortical function. Converging theoretical and experimental evidence indicates that cortical circuits generating self-sustained dynamics operate in an inhibition-stabilized regime. Theoretical work has established that four sets of weights (WE←E, WE←I, WI←E, and WI←I) must obey specific relationships to produce inhibition-stabilized dynamics, but it is not known how the brain can appropriately set the values of all four weight classes in an unsupervised manner to be in the inhibition-stabilized regime. We prove that standard homeostatic plasticity rules are generally unable to generate inhibition-stabilized dynamics and that their instability is caused by a signature property of inhibition-stabilized networks: the paradoxical effect. In contrast, we show that a family of "cross-homeostatic" rules overcome the paradoxical effect and robustly lead to the emergence of stable dynamics. This work provides a model of how-beginning from a silent network-self-sustained inhibition-stabilized dynamics can emerge from learning rules governing all four synaptic weight classes in an orchestrated manner.

Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation.

Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits, neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and nonstimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and nonstimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits and, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.

Time for Memories.

The ability to store information about the past to dynamically predict and prepare for the future is among the most fundamental tasks the brain performs. To date, the problems of understanding how the brain stores and organizes information about the past (memory) and how the brain represents and processes temporal information for adaptive behavior have generally been studied as distinct cognitive functions. This Symposium explores the inherent link between memory and temporal cognition, as well as the potential shared neural mechanisms between them. We suggest that working memory and implicit timing are interconnected and may share overlapping neural mechanisms. Additionally, we explore how temporal structure is encoded in associative and episodic memory and, conversely, the influences of episodic memory on subsequent temporal anticipation and the perception of time. We suggest that neural sequences provide a general computational motif that contributes to timing and working memory, as well as the spatiotemporal coding and recall of episodes.

Study protocol for Early Tracking of Childhood Health determinants (ETCHED): A longitudinal observational life course study.

BACKGROUND: The prevalence of childhood obesity and diabetes continues to rise in the United States (US), especially among minority populations. The objective of the Early Tracking of Childhood Health Determinants (ETCHED) study is to investigate the role of adverse fetal and early-life risk exposures that contribute to the development of childhood obesity and metabolic risk. METHODS: ETCHED is a longitudinal observational study of American Indian/Alaska Native (AI/AN) and Hispanic pregnant woman and their offspring. Pregnant mothers ≥ 18 years old are enrolled at a large public hospital system in the southwestern US. Enrolled mothers are followed through pregnancy, delivery, and the maternal/offspring dyad will be followed until the child's 18th birthday. At each maternal visit, questionnaires assessing medical history, diet, physical activity, sleep, perceived stress, and socioeconomic and sociocultural information are obtained. Standard laboratory tests during maternal visits include glycemic measures, lipids, and renal function. Additional bio samples obtained include venous blood samples and cord blood for obesity/metabolic biomarkers and genetic/epigenetic testing, urinalysis, placental tissue for examining functional pathways, breast milk for metabolomics, and stool for metabolites and microbiome analysis. The offspring will have 6 infant/toddler visits at 6-12 weeks, 4 months, 6 months, 18 months, 2 and 3 years respectively. Thereafter, they will undergo comprehensive research visits (major visits) at 4-5 years, 6-9 years, 10-13 years, and 14-17 years. The major visits in children include detailed medical history, anthropometry, developmental assessment, socioeconomic and environmental assessments (food insecurity, family structure, and childcare), feeding and activity, biochemical tests, genetics/epigenetic testing, and ultrasound elastography. Electronic health records will be reviewed for additional clinical information. The primary analysis will constitute estimation of correlation coefficients between continuous variables. The planned study duration in this ongoing study is 23-years. DISCUSSION: This is a life course study that that will examine biological and environmental risk factors for obesity and cardiometabolic risk from the intrauterine period to early childhood and adolescence in a population with high-risk of obesity and type 2 diabetes in the United States. The ETCHED study would also provide a unique opportunity to combine multi-omics and clinical data to create novel integrative models to predict the cardiometabolic risk associated with childhood obesity and possibly identify etiopathogenetic mechanisms and future targets of intervention. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov identifier: NCT03481829. Updated July 19, 2024, https://clinicaltrials.gov/study/NCT03481829?cond=ETCHED&rank=1 .

Neural Sequences and the Encoding of Time.

Converging experimental and computational evidence indicate that on the scale of seconds the brain encodes time through changing patterns of neural activity. Experimentally, two general forms of neural dynamic regimes that can encode time have been observed: neural population clocks and ramping activity. Neural population clocks provide a high-dimensional code to generate complex spatiotemporal output patterns, in which each neuron exhibits a nonlinear temporal profile. A prototypical example of neural population clocks are neural sequences, which have been observed across species, brain areas, and behavioral paradigms. Additionally, neural sequences emerge in artificial neural networks trained to solve time-dependent tasks. Here, we examine the role of neural sequences in the encoding of time, and how they may emerge in a biologically plausible manner. We conclude that neural sequences may represent a canonical computational regime to perform temporal computations.

Encoding time in neural dynamic regimes with distinct computational tradeoffs.

Converging evidence suggests the brain encodes time in dynamic patterns of neural activity, including neural sequences, ramping activity, and complex dynamics. Most temporal tasks, however, require more than just encoding time, and can have distinct computational requirements including the need to exhibit temporal scaling, generalize to novel contexts, or robustness to noise. It is not known how neural circuits can encode time and satisfy distinct computational requirements, nor is it known whether similar patterns of neural activity at the population level can exhibit dramatically different computational or generalization properties. To begin to answer these questions, we trained RNNs on two timing tasks based on behavioral studies. The tasks had different input structures but required producing identically timed output patterns. Using a novel framework we quantified whether RNNs encoded two intervals using either of three different timing strategies: scaling, absolute, or stimulus-specific dynamics. We found that similar neural dynamic patterns at the level of single intervals, could exhibit fundamentally different properties, including, generalization, the connectivity structure of the trained networks, and the contribution of excitatory and inhibitory neurons. Critically, depending on the task structure RNNs were better suited for generalization or robustness to noise. Further analysis revealed different connection patterns underlying the different regimes. Our results predict that apparently similar neural dynamic patterns at the population level (e.g., neural sequences) can exhibit fundamentally different computational properties in regards to their ability to generalize to novel stimuli and their robustness to noise-and that these differences are associated with differences in network connectivity and distinct contributions of excitatory and inhibitory neurons. We also predict that the task structure used in different experimental studies accounts for some of the experimentally observed variability in how networks encode time.

Identification of Endometrial Cancer-Specific microRNA Biomarkers in Endometrial Fluid.

Abnormal uterine bleeding is a common benign gynecological complaint and is also the most common symptom of endometrial cancer (EC). Although many microRNAs have been reported in endometrial carcinoma, most of them were identified from tumor tissues obtained at surgery or from cell lines cultured in laboratories. The objective of this study was to develop a method to detect EC-specific microRNA biomarkers from liquid biopsy samples to improve the early diagnosis of EC in women. Endometrial fluid samples were collected during patient-scheduled in-office visits or in the operating room prior to surgery using the same technique performed for saline infusion sonohysterography (SIS). The total RNA was extracted from the endometrial fluid specimens, followed by quantification, reverse transcription, and real-time PCR arrays. The study was conducted in two phases: exploratory phase I and validation phase II. In total, endometrial fluid samples from 82 patients were collected and processed, with 60 matched non-cancer versus endometrial carcinoma patients used in phase I and 22 in phase II. The 14 microRNA biomarkers, out of 84 miRNA candidates, with the greatest variation in expression from phase I, were selected to enter phase II validation and statistical analysis. Among them, three microRNAs had a consistent and substantial fold-change in upregulation (miR-429, miR-183-5p, and miR-146a-5p). Furthermore, four miRNAs (miR-378c, miR-4705, miR-1321, and miR-362-3p) were uniquely detected. This research elucidated the feasibility of the collection, quantification, and detection of miRNA from endometrial fluid with a minimally invasive procedure performed during a patient in-office visit. The screening of a larger set of clinical samples was necessary to validate these early detection biomarkers for endometrial cancer.

Differential Excitability of PV and SST Neurons Results in Distinct Functional Roles in Inhibition Stabilization of Up States.

Up states are the best studied example of an emergent neural dynamic regime. Computational models based on a single class of inhibitory neurons indicate that Up states reflect bistable dynamic systems in which positive feedback is stabilized by strong inhibition and predict a paradoxical effect in which increased drive to inhibitory neurons results in decreased inhibitory activity. To date, however, computational models have not incorporated empirically defined properties of parvalbumin (PV) and somatostatin (SST) neurons. Here we first experimentally characterized the frequency-current (F-I) curves of pyramidal (Pyr), PV, and SST neurons from mice of either sex, and confirmed a sharp difference between the threshold and slopes of PV and SST neurons. The empirically defined F-I curves were incorporated into a three-population computational model that simulated the empirically derived firing rates of pyramidal, PV, and SST neurons. Simulations revealed that the intrinsic properties were sufficient to predict that PV neurons are primarily responsible for generating the nontrivial fixed points representing Up states. Simulations and analytical methods demonstrated that while the paradoxical effect is not obligatory in a model with two classes of inhibitory neurons, it is present in most regimes. Finally, experimental tests validated predictions of the model that the Pyr ↔ PV inhibitory loop is stronger than the Pyr ↔ SST loop.SIGNIFICANCE STATEMENT Many cortical computations, such as working memory, rely on the local recurrent excitatory connections that define cortical circuit motifs. Up states are among the best studied examples of neural dynamic regimes that rely on recurrent excitatory excitation. However, this positive feedback must be held in check by inhibition. To address the relative contribution of PV and SST neurons, we characterized the intrinsic input-output differences between these classes of inhibitory neurons and, using experimental and theoretical methods, show that the higher threshold and gain of PV leads to a dominant role in network stabilization.

Differential Short-Term Plasticity of PV and SST Neurons Accounts for Adaptation and Facilitation of Cortical Neurons to Auditory Tones.

Cortical responses to sensory stimuli are strongly modulated by temporal context. One of the best studied examples of such modulation is sensory adaptation. We first show that in response to repeated tones pyramidal (Pyr) neurons in male mouse auditory cortex (A1) exhibit facilitating and stable responses, in addition to adapting responses. To examine the potential mechanisms underlying these distinct temporal profiles, we developed a reduced spiking model of sensory cortical circuits that incorporated the signature short-term synaptic plasticity (STP) profiles of the inhibitory parvalbumin (PV) and somatostatin (SST) interneurons. The model accounted for all three temporal response profiles as the result of dynamic changes in excitatory/inhibitory balance produced by STP, primarily through shifts in the relative latency of Pyr and inhibitory neurons. Transition between the three response profiles was possible by changing the strength of the inhibitory PV→Pyr and SST→Pyr synapses. The model predicted that a unit's latency would be related to its temporal profile. Consistent with this prediction, the latency of stable units was significantly shorter than that of adapting and facilitating units. Furthermore, because of the history-dependence of STP the model generated a paradoxical prediction: that inactivation of inhibitory neurons during one tone would decrease the response of A1 neurons to a subsequent tone. Indeed, we observed that optogenetic inactivation of PV neurons during one tone counterintuitively decreased the spiking of Pyr neurons to a subsequent tone 400 ms later. These results provide evidence that STP is critical to temporal context-dependent responses in the sensory cortex.SIGNIFICANCE STATEMENT Our perception of speech and music depends strongly on temporal context, i.e., the significance of a stimulus depends on the preceding stimuli. Complementary neural mechanisms are needed to sometimes ignore repetitive stimuli (e.g., the tic of a clock) or detect meaningful repetition (e.g., consecutive tones in Morse code). We modeled a neural circuit that accounts for diverse experimentally-observed response profiles in auditory cortex (A1) neurons, based on known forms of short-term synaptic plasticity (STP). Whether the simulated circuit reduced, maintained, or enhanced its response to repeated tones depended on the relative dominance of two different types of inhibitory cells. The model made novel predictions that were experimentally validated. Results define an important role for STP in temporal context-dependent perception.

The acute effect of the menstrual cycle and oral contraceptive cycle on measures of body composition.

PURPOSE: This study aimed to investigate the effect of fluctuating female hormones during the menstrual cycle (MC) and oral contraceptive (OC) cycle on different measures of body composition. METHODS: Twenty-two women with a natural MC and thirty women currently taking combined monophasic OC were assessed over three phases of the menstrual or oral contraceptive cycle. Body weight, skinfolds, bioelectric impedance analysis (BIA), ultrasound, dual-energy X-ray absorptiometry (DXA), and peripheral quantitative computed tomography (pQCT) measurements were performed to assess body composition. Urine specific gravity (USG) was measured as an indication of hydration, and serum oestradiol and progesterone were measured to confirm cycle phases. RESULTS: Five participants with a natural MC were excluded based on the hormone analysis. For the remaining participants, no significant changes over the MC and OC cycle were found for body weight, USG, skinfolds, BIA, ultrasound and pQCT measures. However, DXA body fat percentage and fat mass were lower in the late follicular phase compared to the mid-luteal phase of the MC, while for the OC cycle, DXA body fat percentage was higher and lean mass lower in the early hormone phase compared with the late hormone phase. CONCLUSION: Our findings suggest that assessment of body fat percentage through BIA and skinfolds may be performed without considering the MC or OC cycle. Body adiposity assessment via DXA, however, may be affected by female hormone fluctuations and therefore, it may be advisable to perform repeat testing using DXA during the same phase of the MC or OC cycle.

Protocol of the Snuggle Bug/Acurrucadito Study: a longitudinal study investigating the influences of sleep-wake patterns and gut microbiome development in infancy on rapid weight gain, an early risk factor for obesity.

BACKGROUND: Overweight, obesity, and associated comorbidities are a pressing global issue among children of all ages, particularly among low-income populations. Rapid weight gain (RWG) in the first 6 months of infancy contributes to childhood obesity. Suboptimal sleep-wake patterns and gut microbiota (GM) have also been associated with childhood obesity, but little is known about their influences on early infant RWG. Sleep may alter the GM and infant metabolism, and ultimately impact obesity; however, data on the interaction between sleep-wake patterns and GM development on infant growth are scarce. In this study, we aim to investigate associations of infant sleep-wake patterns and GM development with RWG at 6 months and weight gain at 12 months. We also aim to evaluate whether temporal interactions exist between infant sleep-wake patterns and GM, and if these relations influence RWG. METHODS: The Snuggle Bug/ Acurrucadito study is an observational, longitudinal study investigating whether 24-h, actigraphy-assessed, sleep-wake patterns and GM development are associated with RWG among infants in their first year. Based on the Ecological Model of Growth, we propose a novel conceptual framework to incorporate sleep-wake patterns and the GM as metabolic contributors for RWG in the context of maternal-infant interactions, and familial and socio-physical environments. In total, 192 mother-infant pairs will be recruited, and sleep-wake patterns and GM development assessed at 3 and 8 weeks, and 3, 6, 9, and 12 months postpartum. Covariates including maternal and child characteristics, family and environmental factors, feeding practices and dietary intake of infants and mothers, and stool-derived metabolome and exfoliome data will be assessed. The study will apply machine learning techniques combined with logistic time-varying effect models to capture infant growth and aid in elucidating the dynamic associations between study variables and RWG. DISCUSSION: Repeated, valid, and objective assessment at clinically and developmentally meaningful intervals will provide robust measures of longitudinal sleep, GM, and growth. Project findings will provide evidence for future interventions to prevent RWG in infancy and subsequent obesity. The work also may spur the development of evidence-based guidelines to address modifiable factors that influence sleep-wake and GM development and prevent childhood obesity.

Relationship between maternal global nutrient restriction during pregnancy and offspring kidney structure and function: a systematic review of animal studies.

Maternal undernutrition during pregnancy is prevalent across the globe, and the origins of many chronic diseases can be traced back to in utero conditions. This systematic review considers the current evidence in animal models regarding the relationship between maternal global nutrient restriction during pregnancy and offspring kidney structure and function. CINAHL, Cochrane, EMBASE, MEDLINE, and Scopus were searched to November 2017. Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines were followed, and articles were screened by two independent reviewers. Twenty-eight studies met the inclusion criteria: 16 studies were on rats, 9 on sheep, 2 on baboons, and 1 on goats. The majority of the rat studies had maternal global nutrient restriction during pregnancy at 50% of ad libitum while restriction for sheep and baboon studies ranged from 50% to 75%. Because of the heterogeneity of outcome measures and the large variation in the age of offspring at followup, no meta-analysis was possible. Common outcome measures included kidney weight, nephron number, glomerular size, glomerular filtration rate, and creatinine clearance. To date, there have been no studies assessing kidney function in large animal models. Most studies were rated as having a high or unknown risk of bias. The current body of evidence in animals suggests that exposure to maternal global nutrient restriction during pregnancy has detrimental effects on offspring kidney structure and function, such as lower kidney weight, lower nephron endowment, larger glomerular size, and lower glomerular filtration rate. Further long-term followup of studies in large animal models investigating kidney function through to adulthood are warranted.

The Efficacy of Chest Compressions in the Bell 407.

OBJECTIVE: The Air Medical industry is fraught with obstacles to patient care and providers can recognize that several sub-groups of patients can provide very challenging scenarios while in flight. However, the patient experiencing cardiac arrest in flight is, by its very nature, one that poses the most severe risk to the patient and provider. This study seeks to explore the capability of a highly trained emergency medical provider to provide adequate chest compressions while in a Bell 407 helicopter. METHODS: 59 participants were evaluated in two separate scenarios. Scenario A consisted of 2 rounds of of 200 chest compressions performed on a flat, uncrowded surface. Scenario B consisted of 200 chest compressions performed in the cabin of a Bell 407. Participants performed 2 rounds of 200 chest compressions. The results were then compared to each other and to the AHA 2010 CPR guidelines. RESULTS: The findings of the study show that compressions performed in the aircraft do not meet AHA guidelines for chest compressions in regard to depth and duration of compressions. The deviation from guideline in regard to rate was found to be not statistically significant. CONCLUSION: Chest compressions performed in a Bell 407 helicopter do not meet AHA guidelines.

Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.

Telling time is fundamental to many forms of learning and behavior, including the anticipation of rewarding events. Although the neural mechanisms underlying timing remain unknown, computational models have proposed that the brain represents time in the dynamics of neural networks. Consistent with this hypothesis, changing patterns of neural activity dynamically in a number of brain areas-including the striatum and cortex-has been shown to encode elapsed time. To date, however, no studies have explicitly quantified and contrasted how well different areas encode time by recording large numbers of units simultaneously from more than one area. Here, we performed large-scale extracellular recordings in the striatum and orbitofrontal cortex of mice that learned the temporal relationship between a stimulus and a reward and reported their response with anticipatory licking. We used a machine-learning algorithm to quantify how well populations of neurons encoded elapsed time from stimulus onset. Both the striatal and cortical networks encoded time, but the striatal network outperformed the orbitofrontal cortex, a finding replicated both in simultaneously and nonsimultaneously recorded corticostriatal datasets. The striatal network was also more reliable in predicting when the animals would lick up to ∼1 s before the actual lick occurred. Our results are consistent with the hypothesis that temporal information is encoded in a widely distributed manner throughout multiple brain areas, but that the striatum may have a privileged role in timing because it has a more accurate "clock" as it integrates information across multiple cortical areas. SIGNIFICANCE STATEMENT: The neural representation of time is thought to be distributed across multiple functionally specialized brain structures, including the striatum and cortex. However, until now, the neural code for time has not been compared quantitatively between these areas. Here, we performed large-scale recordings in the striatum and orbitofrontal cortex of mice trained on a stimulus-reward association task involving a delay period and used a machine-learning algorithm to quantify how well populations of simultaneously recorded neurons encoded elapsed time from stimulus onset. We found that, although both areas encoded time, the striatum consistently outperformed the orbitofrontal cortex. These results suggest that the striatum may refine the code for time by integrating information from multiple inputs.

Encoding Time in Feedforward Trajectories of a Recurrent Neural Network Model.

Brain activity evolves through time, creating trajectories of activity that underlie sensorimotor processing, behavior, and learning and memory. Therefore, understanding the temporal nature of neural dynamics is essential to understanding brain function and behavior. In vivo studies have demonstrated that sequential transient activation of neurons can encode time. However, it remains unclear whether these patterns emerge from feedforward network architectures or from recurrent networks and, furthermore, what role network structure plays in timing. We address these issues using a recurrent neural network (RNN) model with distinct populations of excitatory and inhibitory units. Consistent with experimental data, a single RNN could autonomously produce multiple functionally feedforward trajectories, thus potentially encoding multiple timed motor patterns lasting up to several seconds. Importantly, the model accounted for Weber's law, a hallmark of timing behavior. Analysis of network connectivity revealed that efficiency-a measure of network interconnectedness-decreased as the number of stored trajectories increased. Additionally, the balance of excitation (E) and inhibition (I) shifted toward excitation during each unit's activation time, generating the prediction that observed sequential activity relies on dynamic control of the E/I balance. Our results establish for the first time that the same RNN can generate multiple functionally feedforward patterns of activity as a result of dynamic shifts in the E/I balance imposed by the connectome of the RNN. We conclude that recurrent network architectures account for sequential neural activity, as well as for a fundamental signature of timing behavior: Weber's law.

Hypoxia During Resistance Exercise Does Not Affect Physical Performance, Perceptual Responses, or Neuromuscular Recovery.

Scott, BR, Slattery, KM, Sculley, DV, and Dascombe, BJ. Hypoxia during resistance exercise does not affect physical performance, perceptual responses, or neuromuscular recovery. J Strength Cond Res 32(8): 2174-2182, 2018-This study aimed to determine whether performing resistance exercise in hypoxia affects markers of physical performance, perceptual responses, and neuromuscular function. Fourteen male subjects (age: 24.6 ± 2.7 years; height: 179.7 ± 5.9 cm; body mass: 84.6 ± 11.6 kg) with >2 years resistance training experience performed moderate-load resistance exercise in 2 conditions: normoxia (FIO2 = 0.21) and hypoxia (FIO2 = 0.16). Resistance exercise comprised 3 sets of 10 repetitions of back squats and deadlifts at 60% of 1 repetition maximum (1RM), with 60 seconds inter-set rest. Physical performance was assessed by quantifying velocity and power variables during all repetitions. Perceptual ratings of perceived exertion, physical fatigue, muscle soreness, and overall well-being were obtained during and after exercise. Neuromuscular performance was assessed by vertical jump and isometric mid-thigh pull (IMTP) tasks for up to 48 hours after exercise. Although physical performance declined across sets, there were no differences between conditions. Similarly, perceived exertion and fatigue scores were not different between conditions. Muscle soreness increased from baseline at 24 and 48 hours after exercise in both conditions (p ≤ 0.001). Jump height and IMTP peak force were decreased from baseline immediately after exercise (p ≤ 0.026), but returned to preexercise values after 24 hours. These findings suggest that hypoxic resistance exercise does not affect exercise performance or perceived exercise intensity. In addition, neuromuscular recovery and perceptual markers of training stress were not affected by hypoxia, suggesting that hypoxic resistance training may not add substantially to the training dose experienced.

Running performance in the heat is improved by similar magnitude with pre-exercise cold-water immersion and mid-exercise facial water spray.

This investigation compared the effects of external pre-cooling and mid-exercise cooling methods on running time trial performance and associated physiological responses. Nine trained male runners completed familiarisation and three randomised 5 km running time trials on a non-motorised treadmill in the heat (33°C). The trials included pre-cooling by cold-water immersion (CWI), mid-exercise cooling by intermittent facial water spray (SPRAY), and a control of no cooling (CON). Temperature, cardiorespiratory, muscular activation, and perceptual responses were measured as well as blood concentrations of lactate and prolactin. Performance time was significantly faster with CWI (24.5 ± 2.8 min; P = 0.01) and SPRAY (24.6 ± 3.3 min; P = 0.01) compared to CON (25.2 ± 3.2 min). Both cooling strategies significantly (P < 0.05) reduced forehead temperatures and thermal sensation, and increased muscle activation. Only pre-cooling significantly lowered rectal temperature both pre-exercise (by 0.5 ± 0.3°C; P < 0.01) and throughout exercise, and reduced sweat rate (P < 0.05). Both cooling strategies improved performance by a similar magnitude, and are ergogenic for athletes. The observed physiological changes suggest some involvement of central and psychophysiological mechanisms of performance improvement.

Acute Physiological Responses to Moderate-Load Resistance Exercise in Hypoxia.

Scott, BR, Slattery, KM, Sculley, DV, Lockhart, C, and Dascombe, BJ. Acute physiological responses to moderate-load resistance exercise in hypoxia. J Strength Cond Res 31(7): 1973-1981, 2017-This study assessed whether hypoxia augments anabolic responses to moderate-load resistance exercise. Fourteen trained men performed moderate-load resistance exercise in normoxia (NORM; fraction of inspired oxygen [FIO2] = 21%) and moderate-level hypoxia (MH; FIO2 = 16%). Exercise comprised 3 sets of 10 repetitions of squats and deadlifts at 60% of 1 repetition maximum, with 60-second interset rest. Blood lactate (BLa) was quantified after each exercise, whereas arterial oxygen saturation and heart rate (HR) were assessed after each set. Thigh circumference was measured before and after exercise. Muscle activation and oxygenation were monitored by surface electromyography (EMG) and near-infrared spectroscopy, respectively. Relative BLa concentrations were significantly higher following squats (p = 0.041) and deadlifts (p = 0.002) in MH than NORM. Arterial oxygen saturation was lower after each set in MH compared with NORM (p < 0.001), although HR and thigh circumference were not different between conditions. Integrated EMG was higher in MH than in NORM for the squat during several repetitions (p ≤ 0.032). Measures of muscle oxygen status were not significantly different between conditions (p ≥ 0.247). The main findings from this study suggest that hypoxia during moderate-load resistance exercise augments metabolite accumulation and muscle activation. However, a significant hypoxic dose was not measured at the muscle, possibly because of the moderate level of hypoxia used. The current data support previous hypotheses that have suggested hypoxia can augment some physiological responses that are important for muscular development, and may therefore provide benefit over the equivalent training in normoxia.

A Comparison of Mixed-Method Cooling Interventions on Preloaded Running Performance in the Heat.

Stevens, CJ, Bennett, KJM, Sculley, DV, Callister, R, Taylor, L, and Dascombe, BJ. A comparison of mixed-method cooling interventions on preloaded running performance in the heat. J Strength Cond Res 31(3): 620-629, 2017-The purpose of this investigation was to assess the effect of combining practical methods to cool the body on endurance running performance and physiology in the heat. Eleven trained male runners completed 4 randomized, preloaded running time trials (20 minutes at 70% V[Combining Dot Above]O2max and a 3 km time trial) on a nonmotorized treadmill in the heat (33° C). Trials consisted of precooling by combined cold-water immersion and ice slurry ingestion (PRE), midcooling by combined facial water spray and menthol mouth rinse (MID), a combination of all methods (ALL), and control (CON). Performance time was significantly faster in MID (13.7 ± 1.2 minutes; p < 0.01) and ALL (13.7 ± 1.4 minutes; p = 0.04) but not PRE (13.9 ± 1.4 minutes; p = 0.24) when compared with CON (14.2 ± 1.2 minutes). Precooling significantly reduced rectal temperature (initially by 0.5 ± 0.2° C), mean skin temperature, heart rate and sweat rate, and increased iEMG activity, whereas midcooling significantly increased expired air volume and respiratory exchange ratio compared with control. Significant decreases in forehead temperature, thermal sensation, and postexercise blood prolactin concentration were observed in all conditions compared with control. Performance was improved with midcooling, whereas precooling had little or no influence. Midcooling may have improved performance through an attenuated inhibitory psychophysiological and endocrine response to the heat.

Time in Cortical Circuits.

Time is central to cognition. However, the neural basis for time-dependent cognition remains poorly understood. We explore how the temporal features of neural activity in cortical circuits and their capacity for plasticity can contribute to time-dependent cognition over short time scales. This neural activity is linked to cognition that operates in the present or anticipates events or stimuli in the near future. We focus on deliberation and planning in the context of decision making as a cognitive process that integrates information across time. We progress to consider how temporal expectations of the future modulate perception. We propose that understanding the neural basis for how the brain tells time and operates in time will be necessary to develop general models of cognition. SIGNIFICANCE STATEMENT: Time is central to cognition. However, the neural basis for time-dependent cognition remains poorly understood. We explore how the temporal features of neural activity in cortical circuits and their capacity for plasticity can contribute to time-dependent cognition over short time scales. We propose that understanding the neural basis for how the brain tells time and operates in time will be necessary to develop general models of cognition.