Experience Does Not Equal Expertise in Recognizing Infrequent Incoming Gunfire: Neural Markers for Experience and Task Expertise at Peak Behavioral Performance

For a soldier, decisions to use force can happen rapidly and sometimes lead to undesired consequences. In many of these situations, there is a rapid assessment by the shooter that recognizes a threat and responds to it with return fire. But the neural processes underlying these rapid decisions are largely unknown, especially amongst those with extensive weapons experience and expertise. In this paper, we investigate differences in weapons experts and non-experts during an incoming gunfire detection task. Specifically, we analyzed the electroencephalography (EEG) of eleven expert marksmen/soldiers and eleven non-experts while they listened to an audio scene consisting of a sequence of incoming and non-incoming gunfire events. Subjects were tasked with identifying each event as quickly as possible and committing their choice via a motor response. Contrary to our hypothesis, experts did not have significantly better behavioral performance or faster response time than novices. Rather, novices indicated trends of better behavioral performance than experts. These group differences were more dramatic in the EEG correlates of incoming gunfire detection. Using machine learning, we found condition-discriminating EEG activity among novices showing greater magnitude and covering longer periods than those found in experts. We also compared group-level source reconstruction on the maximum discriminating neural correlates and found that each group uses different neural structures to perform the task. From condition-discriminating EEG and source localization, we found that experts perceive more categorical overlap between incoming and non-incoming gunfire. Consequently, the experts did not perform as well behaviorally as the novices. We explain these unexpected group differences as a consequence of experience with gunfire not being equivalent to expertise in recognizing incoming gunfire.     

Is MHC diversity a better marker for conservation than neutral genetic diversity? A case study of two contrasting dolphin populations

Genetic diversity is essential for populations to adapt to changing environments. Measures of genetic diversity are often based on selectively neutral markers, such as microsatellites. Genetic diversity to guide conservation management, however, is better reflected by adaptive markers, including genes of the major histocompatibility complex (MHC). Our aim was to assess MHC and neutral genetic diversity in two contrasting bottlenose dolphin (Tursiops aduncus) populations in Western Australia—one apparently viable population with high reproductive output (Shark Bay) and one with lower reproductive output that was forecast to decline (Bunbury). We assessed genetic variation in the two populations by sequencing the MHC class II DQB, which encompasses the functionally important peptide binding regions (PBR). Neutral genetic diversity was assessed by genotyping twenty‐three microsatellite loci. We confirmed that MHC is an adaptive marker in both populations. Overall, the Shark Bay population exhibited greater MHC diversity than the Bunbury population—for example, it displayed greater MHC nucleotide diversity. In contrast, the difference in microsatellite diversity between the two populations was comparatively low. Our findings are consistent with the hypothesis that viable populations typically display greater genetic diversity than less viable populations. The results also suggest that MHC variation is more closely associated with population viability than neutral genetic variation. Although the inferences from our findings are limited, because we only compared two populations, our results add to a growing number of studies that highlight the usefulness of MHC as a potentially suitable genetic marker for animal conservation. The Shark Bay population, which carries greater adaptive genetic diversity than the Bunbury population, is thus likely more robust to natural or human‐induced changes to the coastal ecosystem it inhabits.     

Genes are information,so information theory is coming to the aid of evolutionary biology

Speciation is central to evolutionary biology, and to elucidate it, we need to catch the early genetic changes that set nascent taxa on their path to species status (Via 2009 ). That challenge is difficult, of course, for two chief reasons: (i) serendipity is required to catch speciation in the act; and (ii) after a short time span with lingering gene flow, differentiation may be low and/or embodied only in rare alleles that are difficult to sample. In this issue of Molecular Ecology Resources, Smouse et al. ( 2015 ) have noted that optimal assessment of differentiation within and between nascent species should be robust to these challenges, and they identified a measure based on Shannon's information theory that has many advantages for this and numerous other tasks. The Shannon measure exhibits complete additivity of information at different levels of subdivision. Of all the family of diversity measures (‘0’ or allele counts, ‘1’ or Shannon, ‘2’ or heterozygosity, F_ST and related metrics) Shannon's measure comes closest to weighting alleles by their frequencies. For the Shannon measure, rare alleles that represent early signals of nascent speciation are neither down‐weighted to the point of irrelevance, as for level 2 measures, nor up‐weighted to overpowering importance, as for level 0 measures (Chao et al. 2010 , 2015 ). Shannon measures have a long history in population genetics, dating back to Shannon's PhD thesis in 1940 (Crow 2001 ), but have received only sporadic attention, until a resurgence of interest in the last ten years, as reviewed briefly by Smouse et al. ( 2015 ).     

Determinants of the hierarchy of humoral immune responsiveness during ontogeny.

A model system of ontogeny was utilized to investigate the development of humoral immunity in both AKR and BALB/c mice. Lethally irradiated adult mice were reconstituted with syngeneic fetal or neonatal liver. These mice were immunized at various times after reconstitution with a series of eight antigens: the bacteriophages F2, phiX-174, and T4; the hapten carrier complexes 2,4 dinitrophenyl-bovine serum albumin and fluorescein-bovine serum albumin; and the small proteins: hen egg lysozyme, sperm whale myoglobin, and bovine pancreatic ribonuclease. Subsequent antibody production to the antigens was assayed with either a direct or a modified bacteriophage neutralization technique. Individual mice responded to the various antigens in a sequential pattern which was basically the same for all mice within each strain. However, there was a marked difference between the two strains in the time at which they developed responsiveness to myoglobin. In order to begin to delineate the separate roles played by B and T cells in the generation of this hierarchical response pattern during ontogeny, the development of anti-DNP and anti-FTC activity was examined in carrier-primed mice. Results of this experiment indicated that functional B cell specificities for the two haptens arise at different times during ontogeny. Further studies are needed to determine whether the hierarchical pattern of immune responsiveness observed for the other antigens is a function of sequential appearance of B cell specificities, T cell specificities, or both.