How quickly participants respond to a ‘go’ after a ‘warning’ signal is partly determined by the time between the two signals (the foreperiod) and the distribution of foreperiods. According to Multiple Trace Theory of Temporal Preparation (MTP), participants use memory traces of previous foreperiods to prepare for the upcoming go signal. If the processes underlying temporal preparation reflect general encoding and memory principles, transfer effects (the carry-over effect of a previous block’s distribution of foreperiods to the current block) should be observed regardless of the sensory modality in which signals are presented. Despite convincing evidence for transfer effects in the visual domain, only weak evidence for transfer effects has been documented in the auditory domain. Three experiments were conducted to examine whether such differences in results are due to the modality of the stimulus or other procedural factors. In each experiment, two groups of participants were exposed to different foreperiod distributions in the acquisition phase and to the same foreperiod distribution in the transfer phase. Experiment 1 used a choice-reaction time (RT) task and the warning signal remained on until the go signal but there was no evidence for transfer effects. Experiment 2 and 3 used a simple- and choice-RT task, respectively, and there was silence between the warning and go signals. Both experiments revealed evidence for transfer effects which suggests that transfer effects are most evident when there is no auditory stimulation between the warning and go signals.

The menopause transition involves changes in oestrogens and adipose tissue distribution, which may influence female brain health post-menopause. Although increased central fat accumulation is linked to risk of metabolic diseases, adipose tissue also serves as the primary biosynthesis site of oestrogens post-menopause. It is unclear whether different types of adipose tissue play diverging roles in female brain health post-menopause, and whether this depends on lifetime oestrogen exposure, which can have lasting effects on the brain and body even after menopause. Using the UK Biobank sample, we investigated associations between brain characteristics and visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT) in 10,251 post-menopausal females, and assessed whether the relationships varied depending on length of reproductive span (age at menarche to age at menopause). To parse the effects of common genetic variation, we computed polygenic scores for reproductive span. The results showed that higher VAT and ASAT were both associated with higher grey and white matter brain age, and greater white matter hyperintensity load. The associations varied positively with reproductive span, indicating more prominent associations between adipose tissue and brain measures in females with a longer reproductive span. The results could not be fully explained by genetic variation or relevant confounders. Our findings indicate that associations between abdominal adipose tissue and brain health post-menopause may partly depend on individual differences in cumulative oestrogen exposure during reproductive years, emphasising the complexity of neural and endocrine ageing processes in females.

BackgroundObesity is a metabolic condition with increasing prevalence all over the world. Patients with a body mass index (BMI) higher than 30 are considered obese. Obesity is also a risk factor for chronic morbidities such as type 2 diabetes and may increase the risk of developing Alzheimer's disease (AD). Not much is known about longitudinal changes in Alzheimer’s pathology in these patients. We hypothesised that BMI would predict longitudinal pathological alterations derived from imaging parameters.Method252 participants (n=107 obese non‐diabetic patients with BMI>30) cognitively normal (n=80) and with mild cognitive impairment (n=172) were evaluated from the Alzheimer’s Disease Neuroimaging Initiative (Mean age = 73.6 years, SD = 8.0). All participants had two T1‐weighted MPRAGE MRI scans within two‐years (Mean gap=718 days, SD=107). Regional cortical thickness was measured on T1‐MPRAGE using FreeSurfer v.6.0. Individual gray matter density maps were computed using voxel‐based morphometry (VBM) and regional values were sampled in various cortical regions. Regional cortical thickness and gray matter density are expressed as delta values between baseline and followup (Value followup ‐ Value Baseline). Spearman’s correlation coefficients were calculated to assess the relationship between BMI and imaging biomarkers.ResultIn the whole cohort, we found that BMI is significantly negatively correlated with longitudinal changes in cortical thickness in anterior cingulate (ACC, p=0.0073, r=‐0.17) and posterior cingulate (PCC, p=0.0147, r=‐0.15) cortical thickness. We also found that BMI is significantly negatively correlated with longitudinal changes in frontal (p=0.0184, r=‐0.15), parietal (p=0.0057, r=‐0.18) and temporal (p=0.0141, r=‐0.16) gray matter density. When looking only at MCI participants, we found similar results with even stronger correlations. BMI is significantly negatively correlated with delta anterior cingulate (ACC, p=0.0008, r=‐0.25) and posterior cingulate (PCC, p=0.004, r=‐0.22) cortical thickness.ConclusionIn this cohort of obese and non‐obese participants cognitively normal and with MCI, we found that obesity was associated with a longitudinal 2‐years worsening of macrostructural changes. Higher BMI was associated with a higher reduction of cortical thickness and with a decreased gray matter density in several brain regions.