Background: There is a lack of scientific consensus about cancer comorbidity in people with central nervous system (CNS) disorders. This study assesses the co-occurrence of cancers in patients with CNS disorders, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), autism spectrum disorders, Down's syndrome (DS), Huntington's disease (HD), multiple sclerosis (MS), Parkinson's disease (PD) and schizophrenia (SCZ). Method: Comprehensive search in PubMed/MEDLINE, Scopus and ISI Web of Knowledge of the literature published before March 2013. We identified 51 relevant articles from 2,229 discrete references, 50 of which contained data suitable for quantitative synthesis (577,013 participants). Pooled effect sizes (ES) were calculated using multiple random-effects meta-analyses. Sources of heterogeneity and uncertainty were explored by means of subgroup and sensitivity analyses, respectively. Results: The presence of CNS disorders was associated with a reduced co-occurrence of cancer (ES = 0.92; 95% confidence interval, CI: 0.87-0.98; I² = 94.5%). A consistently lower overall co-occurrence of cancer was detected in patients with neurodegenerative disorders (ES = 0.80; 95% CI: 0.75- 0.86; I² = 82.8%), and in those with AD (ES = 0.32; 95% CI: 0.22-0.46; I² = 0.0%), PD (ES = 0.83; 95% CI: 0.76-0.91; I² = 80.0%), MS (ES = 0.91; 95% CI: 0.87-0.95; I² = 30.3%) and HD (ES = 0.53; 95% CI: 0.42-0.67; I² = 56.4%). Patients with DS had a higher overall co-occurrence of cancer (ES = 1.46; 95% CI: 1.08-1.96; I² = 87.9%). No association was observed between cancer and ALS (ES = 0.97; 95% CI: 0.76-1.25; I² = 0.0%) or SCZ (ES = 0.98; 95% CI: 0.90-1.07; I² = 96.3%). Patients with PD, MS and SCZ showed (a) higher co-occurrence of some specific cancers (e.g. PD with melanoma, MS with brain cancers and SCZ with breast cancer), and (b) lower co-occurrence of other specific cancers (e.g. lung, prostate and colorectal cancers in PD; lung and prostate cancers in MS; and melanoma and prostate cancer in SCZ). Conclusion: Increased and decreased co-occurrence of cancer in patients with CNS disorders represents an opportunity to discover biological and non-biological connections between these complex disorders.

The recent history of perceptual experience has been shown to influence subsequent perception. Classically, this dependence on perceptual history has been examined in sensory-adaptation paradigms, wherein prolonged exposure to a particular stimulus (e.g., a vertically oriented grating) produces changes in perception of subsequently presented stimuli (e.g., the tilt aftereffect). More recently, several studies have investigated the influence of shorter perceptual exposure with effects, referred to as serial dependence, being described for a variety of low- and high-level perceptual dimensions. In this study, we examined serial dependence in the processing of dispersion statistics, namely variance—a key descriptor of the environment and indicative of the precision and reliability of ensemble representations. We found two opposite serial dependences operating at different timescales, and likely originating at different processing levels: A positive, Bayesian-like bias was driven by the most recent exposures, dependent on feature-specific decision making and appearing only when high confidence was placed in that decision; and a longer lasting negative bias—akin to an adaptation aftereffect—becoming manifest as the positive bias declined. Both effects were independent of spatial presentation location and the similarity of other close traits, such as mean direction of the visual variance stimulus. These findings suggest that visual variance processing occurs in high-level areas but is also subject to a combination of multilevel mechanisms balancing perceptual stability and sensitivity, as with many different perceptual dimensions.

Further investigations are warranted to clarify this relationship. Earlier detection of the elevated Hcy levels may be an effective intervention to prevent cognitive impairment and dementia.

No abstract

The neural basis of time perception remains unknown. A prominent account is the pacemaker-accumulator model, wherein regular ticks of some physiological or neural pacemaker are read out as time. Putative candidates for the pacemaker have been suggested in physiological processes (heartbeat), or dopaminergic mid-brain neurons, whose activity has been associated with spontaneous blinking. However, such proposals have difficulty accounting for observations that time perception varies systematically with perceptual content. We examined physiological influences on human duration estimates for naturalistic videos between 1–64 seconds using cardiac and eye recordings. Duration estimates were biased by the amount of change in scene content. Contrary to previous claims, heart rate, and blinking were not related to duration estimates. Our results support a recent proposal that tracking change in perceptual classification networks provides a basis for human time perception, and suggest that previous assertions of the importance of physiological factors should be tempered.