The importance of the gut-brain axis in maintaining homeostasis has long been appreciated. However, the past 15 yr have seen the emergence of the microbiota (the trillions of microorganisms within and on our bodies) as one of the key regulators of gut-brain function and has led to the appreciation of the importance of a distinct microbiota-gut-brain axis. This axis is gaining ever more traction in fields investigating the biological and physiological basis of psychiatric, neurodevelopmental, age-related, and neurodegenerative disorders. The microbiota and the brain communicate with each other via various routes including the immune system, tryptophan metabolism, the vagus nerve and the enteric nervous system, involving microbial metabolites such as short-chain fatty acids, branched chain amino acids, and peptidoglycans. Many factors can influence microbiota composition in early life, including infection, mode of birth delivery, use of antibiotic medications, the nature of nutritional provision, environmental stressors, and host genetics. At the other extreme of life, microbial diversity diminishes with aging. Stress, in particular, can significantly impact the microbiota-gut-brain axis at all stages of life. Much recent work has implicated the gut microbiota in many conditions including autism, anxiety, obesity, schizophrenia, Parkinson’s disease, and Alzheimer’s disease. Animal models have been paramount in linking the regulation of fundamental neural processes, such as neurogenesis and myelination, to microbiome activation of microglia. Moreover, translational human studies are ongoing and will greatly enhance the field. Future studies will focus on understanding the mechanisms underlying the microbiota-gut-brain axis and attempt to elucidate microbial-based intervention and therapeutic strategies for neuropsychiatric disorders.

In the scientific literature, there is much evidence of a relationship between age and dexterity, where increased age is related to slower, less nimble and less smooth, less coordinated and less controlled performances. While some suggest that the relationship is a direct consequence of reduced muscle strength associated to increased age, there is a lack of research that has systematically investigated the relationships between age, strength and hand dexterity. Therefore, the aim of this study was to examine the associations between age, grip strength and dexterity. 107 adults (range 18-93 years) completed a series of hand dexterity tasks (i.e. steadiness, line tracking, aiming, and tapping) and a test of maximal grip strength. We performed three phases of analyses. Firstly, we evaluated the simple relationships between pairs of variables; replicating the existing literature; and found significant relationships of increased age and reduced strength; increased age and reduced dexterity, and; reduced strength and reduced dexterity. Secondly, we used standard Multiple Regression (MR) models to determine which of the age and strength factors accounted for the greater variance in dexterity. The results showed that both age and strength made significant contributions to the data variance, but that age explained more of the variance in steadiness and line tracking dexterity, whereas strength explained more of the variance in aiming and tapping dexterity. In a third phase of analysis, we used MR analyses to show an interaction between age and strength on steadiness hand dexterity. Simple Slopes post-hoc analyses showed that the interaction was explained by the middle to older aged adults showing a relationship between reduced strength and reduced hand steadiness, whereas younger aged adults showed no relationship between strength and steadiness hand dexterity. The results are discussed in terms of how age and grip strength predict different types of hand dexterity in adults.

Acute exercise bouts alter resting state functional connectivity (rs-FC) within cognitive, sensorimotor, and affective networks, but it remains unknown how these effects are influenced by exercise intensity. Twenty-five male athletes underwent individual fitness assessments using an incremental treadmill test. On separate days, they performed ‘low’ (35% below lactate threshold) and ‘high’ (20% above lactate threshold) intensity exercise bouts of 30 min. Rs-fMRI and Positive and Negative Affect Scale (PANAS) were acquired before and after each exercise bout. Networks of interest were extracted from twenty-two participants (3 dropouts). Pre-to-post changes and between conditions effects were evaluated using FSL’s randomise by applying repeated measures ANOVA. Results were reported at p < 0.05, corrected for multiple comparisons using threshold free cluster enhancement. PANAS revealed a significant increase in positive mood after both exercise conditions. Significant effects were observed between conditions in the right affective and reward network (ARN), the right fronto parietal network (FPN) and the sensorimotor network (SMN). Pre-to-post comparisons after ‘low’ exercise intensity revealed a significant increase in rs-FC in the left and right FPN, while after ‘high’-intensity exercise rs-FC decreased in the SMN and the dorsal attention network (DAN) and increased in the left ARN. Supporting recent findings, this study is the first to report distinct rs-FC alterations driven by exercise intensity: (i) Increased rs-FC in FPN may indicate beneficial functional plasticity for cognitive/attentional processing, (ii) increased rs-FC in ARN may be linked to endogenous opioid-mediated internal affective states. Finally, (iii) decreased rs-FC in the SMN may signify persistent motor fatigue. The distinct effects on rs-FC fit with theories of transient persistent network alterations after acute exercise bouts that are mediated by different exercise intensities and impact differentially on cognitive/attentional or affective responses.