Using phylogenetic analysis and pairwise comparison of 670 complete hepatitis B virus (HBV) genomes, we demonstrated that nucleotide divergence greater than 7.5% can be used to separate strains into genotypes A–H. Strains can be separated into subgenotypes when two criteria are met: nucleotide divergence of about 4% but less than 7.5% and good bootstrap support. There is a highly statistically significant association between serological subtypes and genotypes (χ2‐test for association, P < 0.0001): adw is associated with genotypes A, B, F, G, and H, adr with C and ayw with D and E. The logistic regression method showed that 1802–1803CG are characteristic of genotypes A, D, and E whereas 1802–1803TT are characteristic of genotypes B, C, and F. 1858C is positively associated with genotypes A, F, and H and 1858T with genotypes B, D, and E. Subgenotypes C2, F1/F4 can be differentiated from subgenotypes C1, F2/F3, respectively, because the latter have 1858C as opposed to 1858T in the former. 1888A was positively associated with subgenotype A1 and TAA at 1817 with genotype G. The Haploplot method revealed high linkage between loci 1858 and 1896 but strong evidence of recombination between loci 1862 and 1896. Loci 1809–1812, 1862, and 1888 may have co‐evolved. Using a computer program, we showed that serological subtype deduced from the S region (position 155–835) and mutations/variations within the basic core promoter/precore region (1653–1900), allowed genotyping of HBV with 97% sensitivity and 99% specificity. Certain subgenotypes or subgenotype groups could also be differentiated. J. Med. Virol. 80:27–46, 2008. © 2007 Wiley‐Liss, Inc.
Adaptive behavior requires integrating prior with current information to anticipate upcoming events. Brain structures related to this computation should bring relevant signals from the recent past into the present. Here we report that rats can integrate the most recent prior information with sensory information, thereby improving behavior on a perceptual decision-making task with outcome-dependent past trial history. We find that anticipatory signals in the orbitofrontal cortex about upcoming choice increase over time and are even present before stimulus onset. These neuronal signals also represent the stimulus and relevant second-order combinations of past state variables. The encoding of choice, stimulus and second-order past state variables resides, up to movement onset, in overlapping populations. The neuronal representation of choice before stimulus onset and its build-up once the stimulus is presented suggest that orbitofrontal cortex plays a role in transforming immediate prior and stimulus information into choices using a compact state-space representation.
How is information distributed across large neuronal populations within a given brain area? Information may be distributed roughly evenly across neuronal populations, so that total information scales linearly with the number of recorded neurons. Alternatively, the neural code might be highly redundant, meaning that total information saturates. Here we investigate how sensory information about the direction of a moving visual stimulus is distributed across hundreds of simultaneously recorded neurons in mouse primary visual cortex. We show that information scales sublinearly due to correlated noise in these populations. We compartmentalized noise correlations into information-limiting and nonlimiting components, then extrapolate to predict how information grows with even larger neural populations. We predict that tens of thousands of neurons encode 95% of the information about visual stimulus direction, much less than the number of neurons in primary visual cortex. These findings suggest that the brain uses a widely distributed, but nonetheless redundant code that supports recovering most sensory information from smaller subpopulations.
Ketamine is a dissociative anesthetic drug, which has more recently emerged as a rapid-acting antidepressant. When acutely administered at subanesthetic doses, ketamine causes cognitive deficits like those observed in patients with schizophrenia, including impaired working memory. Although these effects have been linked to ketamine’s action as an N-methyl-D-aspartate receptor antagonist, it is unclear how synaptic alterations translate into changes in brain microcircuit function that ultimately influence cognition. Here, we administered ketamine to rhesus monkeys during a spatial working memory task set in a naturalistic virtual environment. Ketamine induced transient working memory deficits while sparing perceptual and motor skills. Working memory deficits were accompanied by decreased responses of fast spiking inhibitory interneurons and increased responses of broad spiking excitatory neurons in the lateral prefrontal cortex. This translated into a decrease in neuronal tuning and information encoded by neuronal populations about remembered locations. Our results demonstrate that ketamine differentially affects neuronal types in the neocortex; thus, it perturbs the excitation inhibition balance within prefrontal microcircuits and ultimately leads to selective working memory deficits.
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