Critical flicker fusion thresholds (CFFTs) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases and are thought to underlie a number of visual processing skills, including reading. Here, we compare the impact of two vision-training approaches, one involving contrast sensitivity training and the other directional dot-motion training, compared to an active control group trained on Sudoku. The three training paradigms were compared on their effectiveness for altering CFFT. Directional dot-motion and contrast sensitivity training resulted in significant improvement in CFFT, while the Sudoku group did not yield significant improvement. This finding indicates that dot-motion and contrast sensitivity training similarly transfer to effect changes in CFFT. The results, combined with prior research linking CFFT to high-order cognitive processes such as reading ability, and studies showing positive impact of both dot-motion and contrast sensitivity training in reading, provide a possible mechanistic link of how these different training approaches impact reading abilities.

Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.

Members of the Delphinidae family are widely distributed across the world’s oceans. We used a viral metagenomic approach to identify viruses in orca (Orcinus orca) and short-finned pilot whale (Globicephala macrorhynchus) muscle, kidney, and liver samples from deceased animals. From orca tissue samples (muscle, kidney, and liver), we identified a novel polyomavirus (Polyomaviridae), three cressdnaviruses, and two genomoviruses (Genomoviridae). In the short-finned pilot whale we were able to identify one genomovirus in a kidney sample. The presence of unclassified cressdnavirus within two samples (muscle and kidney) of the same animal supports the possibility these viruses might be widespread within the animal. The orca polyomavirus identified here is the first of its species and is not closely related to the only other dolphin polyomavirus previously discovered. The identification and verification of these viruses expands the current knowledge of viruses that are associated with the Delphinidae family.