Bipolar disorder (BD) is a heritable mental illness with complex etiology. We performed a genome-wide association study (GWAS) of 41,917 BD cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. BD risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics, and anesthetics. Integrating eQTL data implicated 15 genes robustly linked to BD via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of BD subtypes indicated high but imperfect genetic correlation between BD type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of BD, identify novel therapeutic leads, and prioritize genes for functional follow-up studies.

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Any repeatedly performed action is characterized by endogenous variability, affecting both speed and accuracy—for a large part presumably caused by fluctuations in underlying brain and body states. The current research questions concerned (a) whether such states are accessible to us and (b) whether we can act upon this information to reduce variability. For example, when playing a game of darts, there is an implicit assumption that people can wait to throw until they are in the right perceptual-attentional state. If this is true, taking away the ability to self-pace the game should worsen performance. We first tested precisely this assumption asking participants to play darts in a self-paced and a fixed-paced condition. There was no benefit of self-pacing, showing that participants were unable to use such control to improve their performance and reduce their variability. Next, we replicated these findings in 2 computer-based tasks, in which participants performed a rapid action-selection and a visual detection task in 1 self-paced and 3 forced-paced conditions. Over 4 different empirical tests, we show that the self-paced condition did not lead to improved performance or reduced variability, nor to reduced temporal dependencies in the reaction time (RT) series. Overall, it seems that, if people have any access to their fluctuating performance-relevant inner states, this access is limited and not relevant for upcoming performance.

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Adverse experiences early in life are associated with the development of psychiatric illnesses. The hippocampus is likely to play pivotal role in generating these effects: it undergoes significant development during childhood and is extremely reactive to stress. In rodent models, stress in the prepubertal period impairs adult hippocampal neurogenesis (AHN) and behaviours which rely on this process. In normal adult animals, environmental enrichment (EE) is a potent promoter of AHN and hippocampal function. Whether exposure to EE during adolescence can restore normal hippocampal function and AHN following pre-pubertal stress (PPS) is unknown. We investigated EE as a treatment for reduced AHN and hippocampal function following PPS in a rodent model. Stress was administered between post-natal days (PND) 25-27, EE from PND35 to early adulthood, when behavioural testing and assessment of AHN took place. PPS enhanced fear reactions to a CS following a trace fear protocol and reduced the survival of 4-week-old adult-born neurons throughout the adult hippocampus. Furthermore, we show that fewer adult-born neurons were active during recall of the CS stimulus following PPS. All effects were reversed by EE. Our results demonstrate lasting effects of PPS on the hippocampus and highlight the utility of EE during adolescence for restoring normal hippocampal function. EE during adolescence is a promising method of enhancing impaired hippocampal function resulting from early life stress, and due to multiple benefits (low cost, few side effects, widespread availability), should be more thoroughly explored as a treatment option in human sufferers of childhood adversity.

This paper presents a program which identifies the 4-panel LCC equivalent of rice plants using image processing techniques and pattern recognition of the Backpropagation neural network. Images of the fully expanded healthy leaves were captured by digital camera and processed through RGB acquisition, color transformation, image enhancement, image segmentation and feature extraction procedures. The extracted features were computed using basic statistical methods, then served as the input to the neural network for LCC panel identification. Thirty (30) samples of IRR 82372H -Mestiso 26 variety were tested; divided into three sets with 10 leaf samples per field. The system was observed to provide an accuracy of 93.33%.