The impact of the human thalamus on brain-wide information processing.

The thalamus is a small, bilateral structure in the diencephalon that integrates signals from many areas of the CNS. This critical anatomical position allows the thalamus to influence whole-brain activity and adaptive behaviour. However, traditional research paradigms have struggled to attribute specific functions to the thalamus, and it has remained understudied in the human neuroimaging literature. Recent advances in analytical techniques and increased accessibility to large, high-quality data sets have brought forth a series of studies and findings that (re-)establish the thalamus as a core region of interest in human cognitive neuroscience, a field that otherwise remains cortico-centric. In this Perspective, we argue that using whole-brain neuroimaging approaches to investigate the thalamus and its interaction with the rest of the brain is key for understanding systems-level control of information processing. To this end, we highlight the role of the thalamus in shaping a range of functional signatures, including evoked activity, interregional connectivity, network topology and neuronal variability, both at rest and during the performance of cognitive tasks.

Correction: Neural activity induced by sensory stimulation can drive large-scale cerebrospinal fluid flow during wakefulness in humans.

[This corrects the article DOI: 10.1371/journal.pbio.3002035.].

Neural activity induced by sensory stimulation can drive large-scale cerebrospinal fluid flow during wakefulness in humans.

Cerebrospinal fluid (CSF) flow maintains healthy brain homeostasis, facilitating solute transport and the exchange of brain waste products. CSF flow is thus important for brain health, but the mechanisms that control its large-scale movement through the ventricles are not well understood. While it is well established that CSF flow is modulated by respiratory and cardiovascular dynamics, recent work has also demonstrated that neural activity is coupled to large waves of CSF flow in the ventricles during sleep. To test whether the temporal coupling between neural activity and CSF flow is in part due to a causal relationship, we investigated whether CSF flow could be induced by driving neural activity with intense visual stimulation. We manipulated neural activity with a flickering checkerboard visual stimulus and found that we could drive macroscopic CSF flow in the human brain. The timing and amplitude of CSF flow was matched to the visually evoked hemodynamic responses, suggesting neural activity can modulate CSF flow via neurovascular coupling. These results demonstrate that neural activity can contribute to driving CSF flow in the human brain and that the temporal dynamics of neurovascular coupling can explain this effect.

Bonobos and chimpanzees remember familiar conspecifics for decades.

Recognition and memory of familiar conspecifics provides the foundation for complex sociality and is vital to navigating an unpredictable social world [Tibbetts and Dale, Trends Ecol. Evol. 22, 529-537 (2007)]. Human social memory incorporates content about interactions and relationships and can last for decades [Sherry and Schacter, Psychol. Rev. 94, 439-454 (1987)]. Long-term social memory likely played a key role throughout human evolution, as our ancestors increasingly built relationships that operated across distant space and time [Malone et al., Int. J. Primatol. 33, 1251-1277 (2012)]. Although individual recognition is widespread among animals and sometimes lasts for years, little is known about social memory in nonhuman apes and the shared evolutionary foundations of human social memory. In a preferential-looking eye-tracking task, we presented chimpanzees and bonobos (N = 26) with side-by-side images of a previous groupmate and a conspecific stranger of the same sex. Apes' attention was biased toward former groupmates, indicating long-term memory for past social partners. The strength of biases toward former groupmates was not impacted by the duration apart, and our results suggest that recognition may persist for at least 26 y beyond separation. We also found significant but weak evidence that, like humans, apes may remember the quality or content of these past relationships: apes' looking biases were stronger for individuals with whom they had more positive histories of social interaction. Long-lasting social memory likely provided key foundations for the evolution of human culture and sociality as they extended across time, space, and group boundaries.

Differential cortical and subcortical visual processing with eyes shut.

Closing our eyes largely shuts down our ability to see. That said, our eyelids still pass some light, allowing our visual system to coarsely process information about visual scenes, such as changes in luminance. However, the specific impact of eye closure on processing within the early visual system remains largely unknown. To understand how visual processing is modulated when eyes are shut, we used functional magnetic resonance imaging (fMRI) to measure responses to a flickering visual stimulus at high (100%) and low (10%) temporal contrasts, while participants viewed the stimuli with their eyes open or closed. Interestingly, we discovered that eye closure produced a qualitatively distinct pattern of effects across the visual thalamus and visual cortex. We found that with eyes open, low temporal contrast stimuli produced smaller responses across the lateral geniculate nucleus (LGN), primary (V1) and extrastriate visual cortex (V2). However, with eyes closed, we discovered that the LGN and V1 maintained similar blood oxygenation level-dependent (BOLD) responses as the eyes open condition, despite the suppressed visual input through the eyelid. In contrast, V2 and V3 had strongly attenuated BOLD response when eyes were closed, regardless of temporal contrast. Our findings reveal a qualitatively distinct pattern of visual processing when the eyes are closed-one that is not simply an overall attenuation but rather reflects distinct responses across visual thalamocortical networks, wherein the earliest stages of processing preserve information about stimuli but are then gated off downstream in visual cortex.NEW & NOTEWORTHY When we close our eyes coarse luminance information is still accessible by the visual system. Using functional magnetic resonance imaging, we examined whether eyelid closure plays a unique role in visual processing. We discovered that while the LGN and V1 show equivalent responses when the eyes are open or closed, extrastriate cortex exhibited attenuated responses with eye closure. This suggests that when the eyes are closed, downstream visual processing is blind to this information.

Theory of Defect-Induced Crystal Field Perturbations in Rare-Earth Magnets.

We present a theory describing the single-ion anisotropy of rare-earth (RE) magnets in the presence of point defects. Taking the RE-lean 1∶12 magnet class as a prototype, we use first-principles calculations to show how the introduction of Ti substitutions into SmFe_{12} perturbs the crystal field, generating new coefficients due to the lower symmetry of the RE environment. We then demonstrate that these perturbations can be described extremely efficiently using a screened point charge model. We provide analytical expressions for the anisotropy energy that can be straightforwardly implemented in atomistic spin dynamics simulations, meaning that such simulations can be carried out for an arbitrary arrangement of point defects. The significant crystal field perturbations calculated here demonstrate that a sample that is single phase from a structural point of view can nonetheless have a dramatically varying anisotropy profile at the atomistic level if there is compositional disorder, which may influence localized magnetic objects like domain walls or skyrmions.

Current Understanding of the Anatomy, Physiology, and Magnetic Resonance Imaging of Neurofluids: Update From the 2022 "ISMRM Imaging Neurofluids Study group" Workshop in Rome.

Neurofluids is a term introduced to define all fluids in the brain and spine such as blood, cerebrospinal fluid, and interstitial fluid. Neuroscientists in the past millennium have steadily identified the several different fluid environments in the brain and spine that interact in a synchronized harmonious manner to assure a healthy microenvironment required for optimal neuroglial function. Neuroanatomists and biochemists have provided an incredible wealth of evidence revealing the anatomy of perivascular spaces, meninges and glia and their role in drainage of neuronal waste products. Human studies have been limited due to the restricted availability of noninvasive imaging modalities that can provide a high spatiotemporal depiction of the brain neurofluids. Therefore, animal studies have been key in advancing our knowledge of the temporal and spatial dynamics of fluids, for example, by injecting tracers with different molecular weights. Such studies have sparked interest to identify possible disruptions to neurofluids dynamics in human diseases such as small vessel disease, cerebral amyloid angiopathy, and dementia. However, key differences between rodent and human physiology should be considered when extrapolating these findings to understand the human brain. An increasing armamentarium of noninvasive MRI techniques is being built to identify markers of altered drainage pathways. During the three-day workshop organized by the International Society of Magnetic Resonance in Medicine that was held in Rome in September 2022, several of these concepts were discussed by a distinguished international faculty to lay the basis of what is known and where we still lack evidence. We envision that in the next decade, MRI will allow imaging of the physiology of neurofluid dynamics and drainage pathways in the human brain to identify true pathological processes underlying disease and to discover new avenues for early diagnoses and treatments including drug delivery. Evidence level: 1 Technical Efficacy: Stage 3.

EEG-LLAMAS: A low-latency neurofeedback platform for artifact reduction in EEG-fMRI.

Simultaneous EEG-fMRI is a powerful multimodal technique for imaging the brain, but its use in neurofeedback experiments has been limited by EEG noise caused by the MRI environment. Neurofeedback studies typically require analysis of EEG in real time, but EEG acquired inside the scanner is heavily contaminated with ballistocardiogram (BCG) artifact, a high-amplitude artifact locked to the cardiac cycle. Although techniques for removing BCG artifacts do exist, they are either not suited to real-time, low-latency applications, such as neurofeedback, or have limited efficacy. We propose and validate a new open-source artifact removal software called EEG-LLAMAS (Low Latency Artifact Mitigation Acquisition Software), which adapts and advances existing artifact removal techniques for low-latency experiments. We first used simulations to validate LLAMAS in data with known ground truth. We found that LLAMAS performed better than the best publicly-available real-time BCG removal technique, optimal basis sets (OBS), in terms of its ability to recover EEG waveforms, power spectra, and slow wave phase. To determine whether LLAMAS would be effective in practice, we then used it to conduct real-time EEG-fMRI recordings in healthy adults, using a steady state visual evoked potential (SSVEP) task. We found that LLAMAS was able to recover the SSVEP in real time, and recovered the power spectra collected outside the scanner better than OBS. We also measured the latency of LLAMAS during live recordings, and found that it introduced a lag of less than 50 ms on average. The low latency of LLAMAS, coupled with its improved artifact reduction, can thus be effectively used for EEG-fMRI neurofeedback. A limitation of the method is its use of a reference layer, a piece of EEG equipment which is not commercially available, but can be assembled in-house. This platform enables closed-loop experiments which previously would have been prohibitively difficult, such as those that target short-duration EEG events, and is shared openly with the neuroscience community.

The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors.

We introduce a new electroencephalogram (EEG) net, which will allow clinicians to monitor EEG while tracking head motion. Motion during MRI limits patient scans, especially of children with epilepsy. EEG is also severely affected by motion-induced noise, predominantly ballistocardiogram (BCG) noise due to the heartbeat. METHODS: The MotoNet was built using polymer thick film (PTF) EEG leads and motion sensors on opposite sides in the same flex circuit. EEG/motion measurements were made with a standard commercial EEG acquisition system in a 3 Tesla (T) MRI. A Kalman filtering-based BCG correction tool was used to clean the EEG in healthy volunteers. RESULTS: MRI safety studies in 3 T confirmed the maximum heating below 1 °C. Using an MRI sequence with spatial localization gradients only, the position of the head was linearly correlated with the average motion sensor output. Kalman filtering was shown to reduce the BCG noise and recover artifact-clean EEG. CONCLUSIONS: The MotoNet is an innovative EEG net design that co-locates 32 EEG electrodes with 32 motion sensors to improve both EEG and MRI signal quality. In combination with custom gradients, the position of the net can, in principle, be determined. In addition, the motion sensors can help reduce BCG noise.

Disruption of Brainstem Structural Connectivity in REM Sleep Behavior Disorder Using 7 Tesla Magnetic Resonance Imaging.

BACKGROUND: Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is one of the earliest manifestations of α synucleinopathies. Brainstem pathophysiology underlying REM sleep behavior disorder has been described in animal models, yet it is understudied in living humans because of the lack of an in vivo brainstem nuclei atlas and to the limited magnetic resonance imaging (MRI) sensitivity. OBJECTIVE: To investigate brainstem structural connectivity changes in iRBD patients by using an in vivo probabilistic brainstem nuclei atlas and 7 Tesla MRI. METHODS: Structural connectivity of 12 iRBD patients and 12 controls was evaluated by probabilistic tractography. Two-sided Wilcoxon rank-sum test was used to compare the structural connectivity indices across groups. RESULTS: In iRBD, we found impaired (Z = 2.6, P < 0.01) structural connectivity in 14 brainstem nuclei, including the connectivity between REM-on (eg, subcoeruleus [SubC]) and REM sleep muscle atonia (eg, medullary reticular formation) areas. CONCLUSIONS: The brainstem nuclei diagram of impaired connectivity in human iRBD expands animal models and is a promising tool to study and possibly assess prodromal synucleinopathy stages. © 2021 International Parkinson and Movement Disorder Society.

Eye-tracking as a window into primate social cognition.

Over the past decade, noninvasive, restraint-free eye-tracking research with primates has transformed our understanding of primate social cognition. The use of this technology with many primate species allows for the exploration and comparison of how these species attend to and understand social agents and interactions. The ability to compare and contrast the cognitive capacities of various primate species, including humans, provides insight into the evolutionary mechanisms and selective pressures that have likely shaped social cognition in similar and divergent ways across the primate order. In this review, we begin by discussing noninvasive behavioral methods used to measure primate gaze and attention before the introduction of noninvasive, restraint-free eye-tracking methodologies. Next, we focus on findings from recent eye-tracking research on primate social cognition, beginning with simple visual and search mechanisms. We then discuss the results that have built on this basic understanding of how primates view images and videos, exploring discrimination and knowledge of social agents, following social cues, tracking perspectives and predicting behavior, and the combination of eye-tracking and other behavioral and physiological methods. Finally, we discuss some future directions of noninvasive eye-tracking research on primate social cognition and current eye-tracking work-in-progress that builds on these previous studies, investigating underexplored socio-cognitive capacities and utilizing new methodologies.

Parental Perspectives on Immunizations: Impact of the COVID-19 Pandemic on Childhood Vaccine Hesitancy.

Childhood vaccine hesitancy has been studied extensively before the COVID-19 pandemic. The pandemic presented new barriers to pediatric vaccinations. Furthermore, the development of COVID-19 vaccines has complicated factors underlying vaccine hesitancy. We performed a cross-sectional mobile phone-based survey at Children's Hospital Los Angeles querying parents regarding perspectives on vaccines before and during the pandemic. Our primary aim was to understand the impact of the pandemic on routine childhood vaccine hesitancy. Secondarily, we examined intent to vaccinate, COVID-19 vaccine hesitancy, and key contributing demographic factors. Among 252 participants, we found overall increased childhood vaccine hesitancy (p = 0.006), increased risk perception (p = 0.006), and unchanged vaccine confidence during the COVID-19 pandemic. Increased hesitancy did not translate into decreased intent to vaccinate with routine childhood vaccines or influenza vaccines. During the pandemic, households with higher income (50-99 K, > 100 K) correlated with decreased routine childhood vaccine hesitancy, while Hispanic ethnicity and African American race had increased risk perception. For COVID-19 vaccine hesitancy, households with higher income (> 100 K) correlated with decreased hesitancy, while non-White ethnicity and race had increased risk perception. We found that routine childhood vaccine hesitancy increased during the COVID-19 pandemic, mainly due to increased risk perception. Key contributing demographic factors behind both childhood vaccine hesitancy and COVID-19 vaccine hesitancy included household income and race. Understanding factors behind routine childhood vaccine hesitancy is crucial to maintaining pediatric vaccination rates and promoting vaccine confidence during and after the COVID-19 pandemic.

Discovery and Implications of Hidden Atomic-Scale Structure in a Metallic Meteorite.

Iron and its alloys have made modern civilization possible, with metallic meteorites providing one of the human's earliest sources of usable iron as well as providing a window into our solar system's billion-year history. Here highest-resolution tools reveal the existence of a previously hidden FeNi nanophase within the extremely slowly cooled metallic meteorite NWA 6259. This new nanophase exists alongside Ni-poor and Ni-rich nanoprecipitates within a matrix of tetrataenite, the uniaxial, chemically ordered form of FeNi. The ferromagnetic nature of the nanoprecipitates combined with the antiferromagnetic character of the FeNi nanophases gives rise to a complex magnetic state that evolves dramatically with temperature. These observations extend and possibly alter our understanding of celestial metallurgy, provide new knowledge concerning the archetypal Fe-Ni phase diagram and supply new information for the development of new types of sustainable, technologically critical high-energy magnets.

Digital Storytelling: Sharing Palliative Care Experiences as an Innovative Educational Approach.

ABSTRACT: When students are exposed to digital stories about a particular nursing field, they feel more prepared to practice in that field. The purpose of this innovative teaching project was to introduce undergraduate nursing students to palliative care nursing through digital storytelling. Digital interviews with experienced nurses from five specialties were compiled and shared with students. Student responses indicated a positive impact on their professional identity and greater awareness about palliative care. Students benefited from hearing about "real" experiences and exploring diverse specialties and reported that this activity helped decrease their fear, find beauty in death, and value nursing presence.

"I loved interacting with this younger generation": exploring the impact of a virtual service-learning program on social connectedness among older adults during the COVID-19 pandemic.

Pervasive feelings of social isolation and loneliness have been longstanding among up to half of older adults, and have received increased attention amid the COVID-19 pandemic. Programs to address loneliness and facilitate meaningful connections are vital for physical and mental wellbeing. The purpose of this study was to explore older adults' experiences participating as volunteers in the Aging is Very Personal (AIVP) service-learning program in relation to feelings of social connectedness. As part of an interprofessional gerontology course, 112 undergraduate students interviewed 55 older adult volunteers via Zoom on the lived experience of aging. Older adult volunteers were surveyed on their experiences with the COVID-19 pandemic and the virtual AIVP program. Data were analyzed using descriptive statistics and reflexive thematic analysis of open-ended questions. Participants reported participation in AIVP had a positive effect on their mood (86%) and made them feel more socially connected (71%). Six themes summarized their experiences: reduced feelings of social isolation; brought me joy; created meaningful intergenerational relationships; gave me a sense of purpose; facilitated genuine engagement; and created important learning opportunities for future health professionals. Virtual AIVP was identified as a valuable program to improve mood and feelings of social connectedness.

Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics.

Recent studies have demonstrated that fast fMRI can track neural activity well above the temporal limit predicted by the canonical hemodynamic response model. While these findings are promising, the biophysical mechanisms underlying these fast fMRI phenomena remain underexplored. In this study, we discuss two aspects of the hemodynamic response, complementary to several existing hypotheses, that can accommodate faster fMRI dynamics beyond those predicted by the canonical model. First, we demonstrate, using both visual and somatosensory paradigms, that the timing and shape of hemodynamic response functions (HRFs) vary across graded levels of stimulus intensity-with lower-intensity stimulation eliciting faster and narrower HRFs. Second, we show that as the spatial resolution of fMRI increases, voxel-wise HRFs begin to deviate from the canonical model, with a considerable portion of voxels exhibiting faster temporal dynamics than predicted by the canonical HRF. Collectively, both stimulus/task intensity and image resolution can affect the sensitivity of fMRI to fast brain activity, which may partly explain recent observations of fast fMRI signals. It is further noteworthy that, while the present investigations focus on fast neural responses, our findings suggest that a revised hemodynamic model may benefit the many fMRI studies using paradigms with wide ranges of contrast levels (e.g., resting or naturalistic conditions) or with modern, high-resolution MR acquisitions.

Model-based physiological noise removal in fast fMRI.

Recent improvements in the speed and sensitivity of fMRI acquisition techniques suggest that fast fMRI can be used to detect and precisely localize sub-second neural dynamics. This enhanced temporal resolution has enormous potential for neuroscientists. However, physiological noise poses a major challenge for the analysis of fast fMRI data. Physiological noise scales with sensitivity, and its autocorrelation structure is altered in rapidly sampled data, suggesting that new approaches are needed for physiological noise removal in fast fMRI. Existing strategies either rely on external physiological recordings, which can be noisy or difficult to collect, or employ data-driven approaches which make assumptions that may not hold true in fast fMRI. We created a statistical model of harmonic regression with autoregressive noise (HRAN) to estimate and remove cardiac and respiratory noise from the fMRI signal directly. This technique exploits the fact that cardiac and respiratory noise signals are fully sampled (rather than aliasing) when imaging at fast rates, allowing us to track and model physiology over time without requiring external physiological measurements. We then created a joint model of neural hemodynamics, and physiological and autocorrelated noise to more accurately remove noise. We first verified that HRAN accurately estimates cardiac and respiratory dynamics and that our model demonstrates goodness-of-fit in fast fMRI data. In task-driven data, we then demonstrated that HRAN is able to remove physiological noise while leaving the neural signal intact, thereby increasing detection of task-driven voxels. Finally, we established that in both simulations and fast fMRI data HRAN is able to improve statistical inferences as compared with gold-standard physiological noise removal techniques. In conclusion, we created a tool that harnesses the novel information in fast fMRI to remove physiological noise, enabling broader use of the technology to study human brain function.

Resting-state "physiological networks".

Slow changes in systemic brain physiology can elicit large fluctuations in fMRI time series, which manifest as structured spatial patterns of temporal correlations between distant brain regions. Here, we investigated whether such "physiological networks"-sets of segregated brain regions that exhibit similar responses following slow changes in systemic physiology-resemble patterns associated with large-scale networks typically attributed to remotely synchronized neuronal activity. By analyzing a large group of subjects from the 3T Human Connectome Project (HCP) database, we demonstrate brain-wide and noticeably heterogenous dynamics tightly coupled to either respiratory variation or heart rate changes. We show, using synthesized data generated from physiological recordings across subjects, that these physiologically-coupled fluctuations alone can produce networks that strongly resemble previously reported resting-state networks, suggesting that, in some cases, the "physiological networks" seem to mimic the neuronal networks. Further, we show that such physiologically-relevant connectivity estimates appear to dominate the overall connectivity observations in multiple HCP subjects, and that this apparent "physiological connectivity" cannot be removed by the use of a single nuisance regressor for the entire brain (such as global signal regression) due to the clear regional heterogeneity of the physiologically-coupled responses. Our results challenge previous notions that physiological confounds are either localized to large veins or globally coherent across the cortex, therefore emphasizing the necessity to consider potential physiological contributions in fMRI-based functional connectivity studies. The rich spatiotemporal patterns carried by such "physiological" dynamics also suggest great potential for clinical biomarkers that are complementary to large-scale neuronal networks.

Characterizing the plasma metabolome during 14 days of live-high, train-low simulated altitude: A metabolomic approach.

NEW FINDINGS: What is the central question of this study? Does 14 days of live-high, train-low simulated altitude alter an individual's metabolomic/metabolic profile? What is the main finding and its importance? This study demonstrated that ∼200 h of moderate simulated altitude exposure resulted in greater variance in measured metabolites between subject than within subject, which indicates individual variability during the adaptive phase to altitude exposure. In addition, metabolomics results indicate that altitude alters multiple metabolic pathways, and the time course of these pathways is different over 14 days of altitude exposure. These findings support previous literature and provide new information on the acute adaptation response to altitude. ABSTRACT: The purpose of this study was to determine the influence of 14 days of normobaric hypoxic simulated altitude exposure at 3000 m on the human plasma metabolomic profile. For 14 days, 10 well-trained endurance runners (six men and four women; 29 ± 7 years of age) lived at 3000 m simulated altitude, accumulating 196.4 ± 25.6 h of hypoxic exposure, and trained at ∼600 m. Resting plasma samples were collected at baseline and on days 3 and 14 of altitude exposure and stored at -80°C. Plasma samples were analysed using liquid chromatography-high-resolution mass spectrometry to construct a metabolite profile of altitude exposure. Mass spectrometry of plasma identified 36 metabolites, of which eight were statistically significant (false discovery rate probability 0.1) from baseline to either day 3 or day 14. Specifically, changes in plasma metabolites relating to amino acid metabolism (tyrosine and proline), glycolysis (adenosine) and purine metabolism (adenosine) were observed during altitude exposure. Principal component canonical variate analysis showed significant discrimination between group means (P < 0.05), with canonical variate 1 describing a non-linear recovery trajectory from baseline to day 3 and then back to baseline by day 14. Conversely, canonical variate 2 described a weaker non-recovery trajectory and increase from baseline to day 3, with a further increase from day 3 to 14. The present study demonstrates that metabolomics can be a useful tool to monitor metabolic changes associated with altitude exposure. Furthermore, it is apparent that altitude exposure alters multiple metabolic pathways, and the time course of these changes is different over 14 days of altitude exposure.

Iron considerations for the athlete: a narrative review.

Iron plays a significant role in the body, and is specifically important to athletes, since it is a dominant feature in processes such as oxygen transport and energy metabolism. Despite its importance, athlete populations, especially females and endurance athletes, are commonly diagnosed with iron deficiency, suggesting an association between sport performance and iron regulation. Although iron deficiency is most common in female athletes (~ 15-35% athlete cohorts deficient), approximately 5-11% of male athlete cohorts also present with this issue. Furthermore, interest has grown in the mechanisms that influence iron absorption in athletes over the last decade, with the link between iron regulation and exercise becoming a research focus. Specifically, exercise-induced increases in the master iron regulatory hormone, hepcidin, has been highlighted as a contributing factor towards altered iron metabolism in athletes. To date, a plethora of research has been conducted, including investigation into the impact that sex hormones, diet (e.g. macronutrient manipulation), training and environmental stress (e.g. hypoxia due to altitude training) have on an athlete's iron status, with numerous recommendations proposed for consideration. This review summarises the current state of research with respect to the aforementioned factors, drawing conclusions and recommendations for future work.