Decoding face recognition abilities in the human brain.

Why are some individuals better at recognizing faces? Uncovering the neural mechanisms supporting face recognition ability has proven elusive. To tackle this challenge, we used a multimodal data-driven approach combining neuroimaging, computational modeling, and behavioral tests. We recorded the high-density electroencephalographic brain activity of individuals with extraordinary face recognition abilities-super-recognizers-and typical recognizers in response to diverse visual stimuli. Using multivariate pattern analyses, we decoded face recognition abilities from 1 s of brain activity with up to 80% accuracy. To better understand the mechanisms subtending this decoding, we compared representations in the brains of our participants with those in artificial neural network models of vision and semantics, as well as with those involved in human judgments of shape and meaning similarity. Compared to typical recognizers, we found stronger associations between early brain representations of super-recognizers and midlevel representations of vision models as well as shape similarity judgments. Moreover, we found stronger associations between late brain representations of super-recognizers and representations of the artificial semantic model as well as meaning similarity judgments. Overall, these results indicate that important individual variations in brain processing, including neural computations extending beyond purely visual processes, support differences in face recognition abilities. They provide the first empirical evidence for an association between semantic computations and face recognition abilities. We believe that such multimodal data-driven approaches will likely play a critical role in further revealing the complex nature of idiosyncratic face recognition in the human brain.

Identification and characterization of Hand2 upstream genomic enhancers active in developing stomach and limbs.

BACKGROUND: The bHLH transcription factor HAND2 plays important roles in the development of the embryonic heart, face, limbs, and sympathetic and enteric nervous systems. To define how and when HAND2 regulates these developmental systems, requires understanding the transcriptional regulation of Hand2. RESULTS: Remarkably, Hand2 is flanked by an extensive upstream gene desert containing a potentially diverse enhancer landscape. Here, we screened the regulatory interval 200 kb proximal to Hand2 for putative enhancers using evolutionary conservation and histone marks in Hand2-expressing tissues. H3K27ac signatures across embryonic tissues pointed to only two putative enhancer regions showing deep sequence conservation. Assessment of the transcriptional enhancer potential of these elements using transgenic reporter lines uncovered distinct in vivo enhancer activities in embryonic stomach and limb mesenchyme, respectively. Activity of the identified stomach enhancer was restricted to the developing antrum and showed expression within the smooth muscle and enteric neurons. Surprisingly, the activity pattern of the limb enhancer did not overlap Hand2 mRNA but consistently yielded a defined subectodermal anterior expression pattern within multiple transgenic lines. CONCLUSIONS: Together, these results start to uncover the diverse regulatory potential inherent to the Hand2 upstream regulatory interval.

Identification of ancestral gnathostome Gli3 enhancers with activity in mammals.

Abnormal expression of the transcriptional regulator and hedgehog (Hh) signaling pathway effector Gli3 is known to trigger congenital disease, most frequently affecting the central nervous system (CNS) and the limbs. Accurate delineation of the genomic cis-regulatory landscape controlling Gli3 transcription during embryonic development is critical for the interpretation of noncoding variants associated with congenital defects. Here, we employed a comparative genomic analysis on fish species with a slow rate of molecular evolution to identify seven previously unknown conserved noncoding elements (CNEs) in Gli3 intronic intervals (CNE15-21). Transgenic assays in zebrafish revealed that most of these elements drive activities in Gli3 expressing tissues, predominantly the fins, CNS, and the heart. Intersection of these CNEs with human disease associated SNPs identified CNE15 as a putative mammalian craniofacial enhancer, with conserved activity in vertebrates and potentially affected by mutation associated with human craniofacial morphology. Finally, comparative functional dissection of an appendage-specific CNE conserved in slowly evolving fish (elephant shark), but not in teleost (CNE14/hs1586) indicates co-option of limb specificity from other tissues prior to the divergence of amniotes and lobe-finned fish. These results uncover a novel subset of intronic Gli3 enhancers that arose in the common ancestor of gnathostomes and whose sequence components were likely gradually modified in other species during the process of evolutionary diversification.

Validation of Effective Extracellular Vesicles Isolation Methods Adapted to Field Studies in Malaria Endemic Regions.

Malaria affects the poorer regions of the world and is of tremendous health and economic burden for developing countries. Extracellular vesicles (EVs) are small vesicles released by almost any cells in the human body, including malaria infected red blood cells. Recent evidence shows that EVs might contribute to the pathogenesis of malaria. In addition, EVs hold considerable value in biomarker discovery. However, there are still significant gaps in our understanding of EV biology. So far most of our knowledge about EVs in malaria comes from in vitro work. More field studies are required to gain insight into their contribution to the disease and pathogenesis under physiological conditions. However, to perform research on EVs in low-income regions might be challenging due to the lack of appropriate equipment to isolate EVs. Therefore, there is a need to develop and validate EV extraction protocols applicable to poorly equipped laboratories. We established and validated two protocols for EV isolation from cell culture supernatants, rodent and human plasma. We compared polyethylene glycol (PEG) and salting out (SA) with sodium acetate for precipitation of EVs. We then characterized the EVs by Transmission Electron Microscopy (TEM), Western Blot, Size-exclusion chromatography (SEC), bead-based flow cytometry and protein quantification. Both protocols resulted in efficient purification of EVs without the need of expensive material or ultracentrifugation. Furthermore, the procedure is easily scalable to work with large and small sample volumes. Here, we propose that both of our approaches can be used in resource limited countries, therefore further helping to close the gap in knowledge of EVs during malaria.

Psychophysical profiles in super-recognizers.

Facial identity matching ability varies widely, ranging from prosopagnosic individuals (who exhibit profound impairments in face cognition/processing) to so-called super-recognizers (SRs), possessing exceptional capacities. Yet, despite the often consequential nature of face matching decisions-such as identity verification in security critical settings-ability assessments tendentially rely on simple performance metrics on a handful of heterogeneously related subprocesses, or in some cases only a single measured subprocess. Unfortunately, methodologies of this ilk leave contributions of stimulus information to observed variations in ability largely un(der)specified. Moreover, they are inadequate for addressing the qualitative or quantitative nature of differences between SRs' abilities and those of the general population. Here, therefore, we sought to investigate individual differences-among SRs identified using a novel conservative diagnostic framework, and neurotypical controls-by systematically varying retinal availability, bandwidth, and orientation of faces' spatial frequency content in two face matching experiments. Psychophysical evaluations of these parameters' contributions to ability reveal that SRs more consistently exploit the same spatial frequency information, rather than suggesting qualitatively different profiles between control observers and SRs. These findings stress the importance of optimizing procedures for SR identification, for example by including measures quantifying the consistency of individuals' behavior.