Childhood unpredictability and the development of exploration.

Early in development, the process of exploration helps children gather new information that fosters learning about the world. Yet, it is unclear how childhood experiences may influence the way humans approach new learning. What influences decisions to exploit known, familiar options versus trying a novel alternative? We found that childhood unpredictability, characterized by unpredictable caregiving and unstable living environments, was associated with reduced exploratory behavior. This effect holds while controlling for individual differences, including anxiety and stress. Individuals who perceived their childhoods as unpredictable explored less and were instead more likely to repeat previous choices (habitual responding). They were also more sensitive to uncertainty than to potential rewards, even when the familiar options yielded lower rewards. We examined these effects across multiple task contexts and via both in-person (N = 78) and online replication (N = 84) studies among 10- to 13-y-olds. Results are discussed in terms of the potential cascading effects of unpredictable environments on the development of decision-making and the effects of early experience on subsequent learning.

Epigenetic-related transcriptional reprogramming elucidated by identification and validation of a novel reference gene combination for RT-qPCR studies in porcine oocytes of contrasting quality.

BACKGROUND: Reliable RT-qPCR results are dependent on appropriate normalisation. Oocyte maturation studies can be challenging in this respect, as the stage of development can distinctively affect reference gene transcript abundance. The aim of this study was to validate the use of reference genes in oocyte in vitro maturation RT-qPCR studies, and thereafter, examine the abundance of transcripts supporting histone modification during oocyte and early embryo development in oocytes of contrasting quality. METHODS AND RESULTS: Total RNA from oocytes from prepubertal gilts and sows was extracted either directly succeeding follicle aspiration or after 44 h in vitro maturation, followed by RT-qPCR. The stability of YWHAG, HPRT1, ACTB, GAPDH, HMBS and PFKP, was analysed by NormFinder and further cross-validated by assessing results generated following application of different combinations of potential reference genes for normalisation of the RT-qPCR data. Combining ACTB and PFKP generated high stability according to NormFinder and concordant results. Applying this normalisation, gilt derived oocytes displayed significantly higher abundance than oocytes from sows of almost all the epigenetic-related transcripts studied (HDAC2, SIRT1, SALL4, KDM1A, KDM1B, KDM5A), both before and after maturation. CONCLUSIONS: This study identified the combined use of ACTB and PFKP as the optimal normalisation for porcine oocyte RT-qPCR data. In oocytes collected from prepubertal gilts, transcription did not appear to be silenced at the time of aspiration, and accumulation of transcripts supporting histone modification facilitating proper fertilization and further embryo development seemed delayed. The results imply the epigenetic-related transcripts may have potential as markers of oocyte quality.

Combination and competition between path integration and landmark navigation in the estimation of heading direction.

Successful navigation requires the ability to compute one's location and heading from incoming multisensory information. Previous work has shown that this multisensory input comes in two forms: body-based idiothetic cues, from one's own rotations and translations, and visual allothetic cues, from the environment (usually visual landmarks). However, exactly how these two streams of information are integrated is unclear, with some models suggesting the body-based idiothetic and visual allothetic cues are combined, while others suggest they compete. In this paper we investigated the integration of body-based idiothetic and visual allothetic cues in the computation of heading using virtual reality. In our experiment, participants performed a series of body turns of up to 360 degrees in the dark with only a brief flash (300ms) of visual feedback en route. Because the environment was virtual, we had full control over the visual feedback and were able to vary the offset between this feedback and the true heading angle. By measuring the effect of the feedback offset on the angle participants turned, we were able to determine the extent to which they incorporated visual feedback as a function of the offset error. By further modeling this behavior we were able to quantify the computations people used. While there were considerable individual differences in performance on our task, with some participants mostly ignoring the visual feedback and others relying on it almost entirely, our modeling results suggest that almost all participants used the same strategy in which idiothetic and allothetic cues are combined when the mismatch between them is small, but compete when the mismatch is large. These findings suggest that participants update their estimate of heading using a hybrid strategy that mixes the combination and competition of cues.

Path integration in large-scale space and with novel geometries: Comparing vector addition and encoding-error models.

Path integration is thought to rely on vestibular and proprioceptive cues yet most studies in humans involve primarily visual input, providing limited insight into their respective contributions. We developed a paradigm involving walking in an omnidirectional treadmill in which participants were guided on two sides of a triangle and then found their back way to origin. In Experiment 1, we tested a range of different triangle types while keeping the distance of the unguided side constant to determine the influence of spatial geometry. Participants overshot the angle they needed to turn and undershot the distance they needed to walk, with no consistent effect of triangle type. In Experiment 2, we manipulated distance while keeping angle constant to determine how path integration operated over both shorter and longer distances. Participants underestimated the distance they needed to walk to the origin, with error increasing as a function of the walked distance. To attempt to account for our findings, we developed configural-based computational models involving vector addition, the second of which included terms for the influence of past trials on the current one. We compared against a previously developed configural model of human path integration, the Encoding-Error model. We found that the vector addition models captured the tendency of participants to under-encode guided sides of the triangles and an influence of past trials on current trials. Together, our findings expand our understanding of body-based contributions to human path integration, further suggesting the value of vector addition models in understanding these important components of human navigation.

Accumulation Dynamics of Transcripts and Proteins of Cold-Responsive Genes in Fragaria vesca Genotypes of Differing Cold Tolerance.

Identifying and characterizing cold responsive genes in Fragaria vesca associated with or responsible for low temperature tolerance is a vital part of strawberry cultivar development. In this study we have investigated the transcript levels of eight genes, two dehydrin genes, three putative ABA-regulated genes, two cold-inducible CBF genes and the alcohol dehydrogenase gene, extracted from leaf and crown tissues of three F. vesca genotypes that vary in cold tolerance. Transcript levels of the CBF/DREB1 transcription factor FvCBF1E exhibited stronger cold up-regulation in comparison to FvCBF1B.1 in all genotypes. Transcripts of FvADH were highly up-regulated in both crown and leaf tissues from all three genotypes. In the 'ALTA' genotype, FvADH transcripts were significantly higher in leaf than crown tissues and more than 10 to 20-fold greater than in the less cold-tolerant 'NCGR1363' and 'FDP817' genotypes. FvGEM, containing the conserved ABRE promoter element, transcript was found to be cold-regulated in crowns. Direct comparison of the kinetics of transcript and protein accumulation of dehydrins was scrutinized. In all genotypes and organs, the changes of XERO2 transcript levels generally preceded protein changes, while levels of COR47 protein accumulation preceded the increases in COR47 RNA in 'ALTA' crowns.

The Phishing Email Suspicion Test (PEST) a lab-based task for evaluating the cognitive mechanisms of phishing detection.

Phishing emails constitute a major problem, linked to fraud and exploitation as well as subsequent negative health outcomes including depression and suicide. Because of their sheer volume, and because phishing emails are designed to deceive, purely technological solutions can only go so far, leaving human judgment as the last line of defense. However, because it is difficult to phish people in the lab, little is known about the cognitive and neural mechanisms underlying phishing susceptibility. There is therefore a critical need to develop an ecologically valid lab-based measure of phishing susceptibility that will allow evaluation of the cognitive mechanisms involved in phishing detection. Here we present such a measure based on a task, the Phishing Email Suspicion Test (PEST), and a cognitive model to quantify behavior. In PEST, participants rate a series of phishing and non-phishing emails according to their level of suspicion. By comparing suspicion scores for each email to its real-world efficacy, we find initial support for the ecological validity of PEST - phishing emails that were more effective in the real world were more effective at deceiving people in the lab. In the proposed computational model, we quantify behavior in terms of participants' overall level of suspicion of emails, their ability to distinguish phishing from non-phishing emails, and the extent to which emails from the recent past bias their current decision. Together, our task and model provide a framework for studying the cognitive neuroscience of phishing detection.

Clinical, genetic, and structural basis of apparent mineralocorticoid excess due to 11ß-hydroxysteroid dehydrogenase type 2 deficiency.

Mutations in 11ß-hydroxysteroid dehydrogenase type 2 gene (HSD11B2) cause an extraordinarily rare autosomal recessive disorder, apparent mineralocorticoid excess (AME). AME is a form of low renin hypertension that is potentially fatal if untreated. Mutations in the HSD11B2 gene result either in severe AME or a milder phenotype (type 2 AME). To date, ∼40 causative mutations have been identified. As part of the International Consortium for Rare Steroid Disorders, we have diagnosed and followed the largest single worldwide cohort of 36 AME patients. Here, we present the genotype and clinical phenotype of these patients, prominently from consanguineous marriages in the Middle East, who display profound hypertension and hypokalemic alkalosis. To correlate mutations with phenotypic severity, we constructed a computational model of the HSD11B2 protein. Having used a similar strategy for the in silico evaluation of 150 mutations of CYP21A2, the disease-causing gene in congenital adrenal hyperplasia, we now provide a full structural explanation for the clinical severity of AME resulting from each known HSD11B2 missense mutation. We find that mutations that allow the formation of an inactive dimer, alter substrate/coenzyme binding, or impair structural stability of HSD11B2 yield severe AME. In contrast, mutations that cause an indirect disruption of substrate binding or mildly alter intramolecular interactions result in type 2 AME. A simple in silico evaluation of novel missense mutations could help predict the often-diverse phenotypes of an extremely rare monogenic disorder.

DNA methylation patterns vary in boar sperm cells with different levels of DNA fragmentation.

BACKGROUND: Sperm DNA integrity is considered essential for successful transmission of the paternal genome, fertilization and normal embryo development. DNA fragmentation index (DFI, %) has become a key parameter in the swine artificial insemination industry to assess sperm DNA integrity. Recently, in some elite Norwegian Landrace boars (boars with excellent field fertility records), a higher level of sperm DFI has been observed. In order to obtain a better understanding of this, and to study the complexity of sperm DNA integrity, liquid preserved semen samples from elite boars with contrasting DFI levels were examined for protamine deficiency, thiol profile and disulphide bonds. Additionally, the DNA methylation profiles of the samples were determined by reduced representation bisulphite sequencing (RRBS). RESULTS: In this study, different traits related to sperm DNA integrity were investigated (n = 18 ejaculates). Upon liquid storage, the levels of total thiols and disulphide bonds decreased significantly, while the DFI and protamine deficiency level increased significantly. The RRBS results revealed similar global patterns of low methylation from semen samples with different levels of DFI (low, medium and high). Differential methylation analyses indicated that the number of differentially methylated cytosines (DMCs) increased in the low-high compared to the low-medium and the medium-high DFI groups. Annotating the DMCs with gene and CpG features revealed clear differences between DFI groups. In addition, the number of annotated transcription starting sites (TSS) and associated pathways in the low-high comparison was greater than the other two groups. Pathway analysis showed that genes (based on the closest TSS to DMCs) corresponding to low-high DFI comparison were associated with important processes such as membrane function, metabolic cascade and antioxidant defence system. CONCLUSION: To our knowledge, this is the first study evaluating DNA methylation in boar sperm cells with different levels of DFI. The present study shows that sperm cells with varying levels of DNA fragmentation exhibit similar global methylation, but different site-specific DNA methylation signatures. Moreover, with increasing DNA fragmentation in spermatozoa, there is an increase in the number of potentially affected downstream genes and their respective regulatory pathways.

Loss of skin elasticity is associated with pulmonary emphysema, biomarkers of inflammation, and matrix metalloproteinase activity in smokers.

BACKGROUND: Elastin breakdown and the resultant loss of lung elastic recoil is a hallmark of pulmonary emphysema in susceptible individuals as a consequence of tobacco smoke exposure. Systemic alterations to the synthesis and degradation of elastin may be important to our understanding of disease phenotypes in chronic obstructive pulmonary disease. We investigated the association of skin elasticity with pulmonary emphysema, obstructive lung disease, and blood biomarkers of inflammation and tissue protease activity in tobacco-exposed individuals. METHODS: Two hundred and thirty-six Caucasian individuals were recruited into a sub-study of the University of Pittsburgh Specialized Center for Clinically Orientated Research in chronic obstructive pulmonary disease, a prospective cohort study of current and former smokers. The skin viscoelastic modulus (VE), a determinant of skin elasticity, was recorded from the volar forearm and facial wrinkling severity was determined using the Daniell scoring system. RESULTS: In a multiple regression analysis, reduced VE was significantly associated with cross-sectional measurement of airflow obstruction (FEV1/FVC) and emphysema quantified from computed tomography (CT) images, ß = 0.26, p = 0.001 and ß = 0.24, p = 0.001 respectively. In emphysema-susceptible individuals, elasticity-determined skin age was increased (median 4.6 years) compared to the chronological age of subjects without emphysema. Plasma biomarkers of inflammation (TNFR1, TNFR2, CRP, PTX3, and SAA) and matrix metalloproteinase activity (MMP1, TIMP1, TIMP2, and TIMP4) were inversely associated with skin elasticity. CONCLUSIONS: We report that an objective non-invasive determinant of skin elasticity is independently associated with measures of lung function, pulmonary emphysema, and biomarkers of inflammation and tissue proteolysis in tobacco-exposed individuals. Loss of skin elasticity is a novel observation that may link the common pathological processes that drive tissue elastolysis in the extracellular matrix of the skin and lung in emphysema-susceptible individuals.

ErbB4 promotes malignant peripheral nerve sheath tumor pathogenesis via Ras-independent mechanisms.

BACKGROUND: We have found that erbB receptor tyrosine kinases drive Ras hyperactivation and growth in NF1-null malignant peripheral nerve sheath tumors (MPNSTs). However, MPNSTs variably express multiple erbB receptors with distinct functional characteristics and it is not clear which of these receptors drive MPNST pathogenesis. Here, we test the hypothesis that altered erbB4 expression promotes MPNST pathogenesis by uniquely activating key cytoplasmic signaling cascades. METHODS: ErbB4 expression was assessed using immunohistochemistry, immunocytochemistry, immunoblotting and real-time PCR. To define erbB4 functions, we generated mice that develop MPNSTs with floxed Erbb4 alleles (P0-GGFß3;Trp53+/-;Erbb4flox/flox mice) and ablated Erbb4 in these tumors. MPNST cell proliferation and survival was assessed using 3H-thymidine incorporation, MTT assays, Real-Time Glo and cell count assays. Control and Erbb4-null MPNST cells were orthotopically xenografted in immunodeficient mice and the growth, proliferation (Ki67 labeling), apoptosis (TUNEL labeling) and angiogenesis of these grafts was analyzed. Antibody arrays querying cytoplasmic kinases were used to identify erbB4-responsive kinases. Pharmacologic or genetic inhibition was used to identify erbB4-responsive kinases that drive proliferation. RESULTS: Aberrant erbB4 expression was evident in 25/30 surgically resected human MPNSTs and in MPNSTs from genetically engineered mouse models (P0-GGFß3 and P0-GGFß3;Trp53+/- mice); multiple erbB4 splice variants that differ in their ability to activate PI3 kinase and nuclear signaling were present in MPNST-derived cell lines. Erbb4-null MPNST cells demonstrated decreased proliferation and survival and altered morphology relative to non-ablated controls. Orthotopic allografts of Erbb4-null cells were significantly smaller than controls, with reduced proliferation, survival and vascularization. ERBB4 knockdown in human MPNST cells similarly inhibited DNA synthesis and viability. Although we have previously shown that broad-spectrum erbB inhibitors inhibit Ras activation, Erbb4 ablation did not affect Ras activation, suggesting that erbB4 drives neoplasia via non-Ras dependent pathways. An analysis of 43 candidate kinases identified multiple NRG1ß-responsive and erbB4-dependent signaling cascades including the PI3K, WNK1, STAT3, STAT5 and phospholipase-Cγ pathways. Although WNK1 inhibition did not alter proliferation, inhibition of STAT3, STAT5 and phospholipase-Cγ markedly reduced proliferation. CONCLUSIONS: ErbB4 promotes MPNST growth by activating key non-Ras dependent signaling cascades including the STAT3, STAT5 and phospholipase-Cγ pathways. ErbB4 and its effector pathways are thus potentially useful therapeutic targets in MPNSTs.

Correction: A Mixture of Delta-Rules Approximation to Bayesian Inference in Change-Point Problems.

[This corrects the article DOI: 10.1371/journal.pcbi.1003150.].

Prediction in infants and adults: A pupillometry study.

Adults use both bottom-up sensory inputs and top-down signals to generate predictions about future sensory inputs. Infants have also been shown to make predictions with simple stimuli and recent work has suggested top-down processing is available early in infancy. However, it is unknown whether this indicates that top-down prediction is an ability that is continuous across the lifespan or whether an infant's ability to predict is different from an adult's, qualitatively or quantitatively. We employed pupillometry to provide a direct comparison of prediction abilities across these disparate age groups. Pupil dilation response (PDR) was measured in 6-month olds and adults as they completed an identical implicit learning task designed to help learn associations between sounds and pictures. We found significantly larger PDR for visual omission trials (i.e. trials that violated participants' predictions without the presentation of new stimuli to control for bottom-up signals) compared to visual present trials (i.e. trials that confirmed participants' predictions) in both age groups. Furthermore, a computational learning model that is closely linked to prediction error (Rescorla-Wagner model) demonstrated similar learning trajectories suggesting a continuity of predictive capacity and learning across the two age groups.

Catecholamine-Mediated Increases in Gain Enhance the Precision of Cortical Representations.

UNLABELLED: Neurophysiological evidence suggests that neuromodulators, such as norepinephrine and dopamine, increase neural gain in target brain areas. Computational models and prominent theoretical frameworks indicate that this should enhance the precision of neural representations, but direct empirical evidence for this hypothesis is lacking. In two functional MRI studies, we examine the effect of baseline catecholamine levels (as indexed by pupil diameter and manipulated pharmacologically) on the precision of object representations in the human ventral temporal cortex using angular dispersion, a powerful, multivariate metric of representational similarity (precision). We first report the results of computational model simulations indicating that increasing catecholaminergic gain should reduce the angular dispersion, and thus increase the precision, of object representations from the same category, as well as reduce the angular dispersion of object representations from distinct categories when distinct-category representations overlap. In Study 1 (N = 24), we show that angular dispersion covaries with pupil diameter, an index of baseline catecholamine levels. In Study 2 (N = 24), we manipulate catecholamine levels and neural gain using the norepinephrine transporter blocker atomoxetine and demonstrate consistent, causal effects on angular dispersion and brain-wide functional connectivity. Despite the use of very different methods of examining the effect of baseline catecholamine levels, our results show a striking convergence and demonstrate that catecholamines increase the precision of neural representations. SIGNIFICANCE STATEMENT: Norepinephrine and dopamine are among the most widely distributed and ubiquitous neuromodulators in the mammalian brain and have a profound and pervasive impact on cognition. Baseline catecholamine levels tend to increase with increasing task engagement in tasks involving perceptual decisions, yet there is currently no direct evidence of the specific impact of these increases in catecholamine levels on perceptual encoding. Our results fill this void by showing that catecholamines enhance the precision of encoding cortical object representations, and by suggesting that this effect is mediated by increases in neural gain, thus offering a mechanistic account of our key finding.

Increased locus coeruleus tonic activity causes disengagement from a patch-foraging task.

High levels of locus coeruleus (LC) tonic activity are associated with distraction and poor performance within a task. Adaptive gain theory (AGT; Aston-Jones & Cohen, 2005) suggests that this may reflect an adaptive function of the LC, encouraging search for more remunerative opportunities in times of low utility. Here, we examine whether stimulating LC tonic activity using designer receptors (DREADDs) promotes searching for better opportunities in a patch-foraging task as the value of a patch diminishes. The task required rats to decide repeatedly whether to exploit an immediate but depleting reward within a patch or to incur the cost of a time delay to travel to a new, fuller patch. Similar to behavior associated with high LC tonic activity in other tasks, we found that stimulating LC tonic activity impaired task performance, resulting in reduced task participation and increased response times and omission rates. However, this was accompanied by a more specific, predicted effect: a significant tendency to leave patches earlier, which was best explained by an increase in decision noise rather than a systematic bias to leave earlier (i.e., at higher values). This effect is consistent with the hypothesis that high LC tonic activity favors disengagement from current behavior, and the pursuit of alternatives, by augmenting processing noise. These results provide direct causal evidence for the relationship between LC tonic activity and flexible task switching proposed by AGT.

Complementary feature selection from alternative splicing events and gene expression for phenotype prediction.

MOTIVATION: A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via gene expression. Isoforms, however, generated from alternative splicing, may provide a novel and complementary set of transcripts for phenotype prediction. In contrast to gene expression, the number of isoforms increases significantly due to numerous alternative splicing patterns, resulting in a prioritization problem for many machine learning algorithms. This study identifies the empirically optimal methods of transcript quantification, feature engineering and filtering steps using phenotype prediction accuracy as a metric. At the same time, the complementary nature of gene and isoform data is analyzed and the feasibility of identifying isoforms as biomarker candidates is examined. RESULTS: Isoform features are complementary to gene features, providing non-redundant information and enhanced predictive power when prioritized and filtered. A univariate filtering algorithm, which selects up to the N highest ranking features for phenotype prediction is described and evaluated in this study. An empirical comparison of pipelines for isoform quantification is reported by performing cross-validation prediction tests with datasets from human non-small cell lung cancer (NSCLC) patients, human patients with chronic obstructive pulmonary disease (COPD) and amyotrophic lateral sclerosis (ALS) transgenic mice, each including samples of diseased and non-diseased phenotypes. AVAILABILITY AND IMPLEMENTATION: https://github.com/clabuzze/Phenotype-Prediction-Pipeline.git CONTACT: clabuzze@iastate.edu, antoniom@bc.edu, watsondk@musc.edu, andersonpe2@cofc.edu.

Reinforcement learning in multidimensional environments relies on attention mechanisms.

In recent years, ideas from the computational field of reinforcement learning have revolutionized the study of learning in the brain, famously providing new, precise theories of how dopamine affects learning in the basal ganglia. However, reinforcement learning algorithms are notorious for not scaling well to multidimensional environments, as is required for real-world learning. We hypothesized that the brain naturally reduces the dimensionality of real-world problems to only those dimensions that are relevant to predicting reward, and conducted an experiment to assess by what algorithms and with what neural mechanisms this "representation learning" process is realized in humans. Our results suggest that a bilateral attentional control network comprising the intraparietal sulcus, precuneus, and dorsolateral prefrontal cortex is involved in selecting what dimensions are relevant to the task at hand, effectively updating the task representation through trial and error. In this way, cortical attention mechanisms interact with learning in the basal ganglia to solve the "curse of dimensionality" in reinforcement learning.

Multivariate models from RNA-Seq SNVs yield candidate molecular targets for biomarker discovery: SNV-DA.

BACKGROUND: It has recently been shown that significant and accurate single nucleotide variants (SNVs) can be reliably called from RNA-Seq data. These may provide another source of features for multivariate predictive modeling of disease phenotype for the prioritization of candidate biomarkers. The continuous nature of SNV allele fraction features allows the concurrent investigation of several genomic phenomena, including allele specific expression, clonal expansion and/or deletion, and copy number variation. RESULTS: The proposed software pipeline and package, SNV Discriminant Analysis (SNV-DA), was applied on two RNA-Seq datasets with varying sample sizes sequenced at different depths: a dataset containing primary tumors from twenty patients with different disease outcomes in lung adenocarcinoma and a larger dataset of primary tumors representing two major breast cancer subtypes, estrogen receptor positive and triple negative. Predictive models were generated using the machine learning algorithm, sparse projections to latent structures discriminant analysis. Training sets composed of RNA-Seq SNV features limited to genomic regions of origin (e.g. exonic or intronic) and/or RNA-editing sites were shown to produce models with accurate predictive performances, were discriminant towards true label groupings, and were able to produce SNV rankings significantly different from than univariate tests. Furthermore, the utility of the proposed methodology is supported by its comparable performance to traditional models as well as the enrichment of selected SNVs located in genes previously associated with cancer and genes showing allele-specific expression. As proof of concept, we highlight the discovery of a previously unannotated intergenic locus that is associated with epigenetic regulatory marks in cancer and whose significant allele-specific expression is correlated with ER+ status; hereafter named ER+ associated hotspot (ERPAHS). CONCLUSION: The use of models from RNA-Seq SNVs to identify and prioritize candidate molecular targets for biomarker discovery is supported by the ability of the proposed method to produce significantly accurate predictive models that are discriminant towards true label groupings. Importantly, the proposed methodology allows investigation of mutations outside of exonic regions and identification of interesting expressed loci not included in traditional gene annotations. An implementation of the proposed methodology is provided that allows the user to specify SNV filtering criteria and cross-validation design during model creation and evaluation.

Is Model Fitting Necessary for Model-Based fMRI?

Model-based analysis of fMRI data is an important tool for investigating the computational role of different brain regions. With this method, theoretical models of behavior can be leveraged to find the brain structures underlying variables from specific algorithms, such as prediction errors in reinforcement learning. One potential weakness with this approach is that models often have free parameters and thus the results of the analysis may depend on how these free parameters are set. In this work we asked whether this hypothetical weakness is a problem in practice. We first developed general closed-form expressions for the relationship between results of fMRI analyses using different regressors, e.g., one corresponding to the true process underlying the measured data and one a model-derived approximation of the true generative regressor. Then, as a specific test case, we examined the sensitivity of model-based fMRI to the learning rate parameter in reinforcement learning, both in theory and in two previously-published datasets. We found that even gross errors in the learning rate lead to only minute changes in the neural results. Our findings thus suggest that precise model fitting is not always necessary for model-based fMRI. They also highlight the difficulty in using fMRI data for arbitrating between different models or model parameters. While these specific results pertain only to the effect of learning rate in simple reinforcement learning models, we provide a template for testing for effects of different parameters in other models.

Genotype-phenotype correlation in 1,507 families with congenital adrenal hyperplasia owing to 21-hydroxylase deficiency.

Over the last two decades, we have extensively studied the genetics of congenital adrenal hyperplasia caused by 21-hydroxylase deficiency (CAH) and have performed 8,290 DNA analyses of the CYP21A2 gene on members of 4,857 families at risk for CAH--the largest cohort of CAH patients reported to date. Of the families studied, 1,507 had at least one member affected with one of three known forms of CAH, namely salt wasting, simple virilizing, or nonclassical CAH. Here, we report the genotype and phenotype of each affected patient, as well as the ethnic group and country of origin for each patient. We showed that 21 of 45 genotypes yielded a phenotypic correlation in our patient cohort. In particular, contrary to what is generally reported in the literature, we found that certain mutations, for example, the P30L, I2G, and I172N mutations, yielded different CAH phenotypes. In salt wasting and nonclassical CAH, a phenotype can be attributed to a genotype; however, in simple virilizing CAH, we observe wide phenotypic variability, particularly with the exon 4 I172N mutation. Finally, there was a high frequency of homozygous I2G and V281L mutations in Middle Eastern and Ashkenazi Jewish populations, respectively. By identifying the predominant phenotype for a given genotype, these findings should assist physicians in prenatal diagnosis and genetic counseling of parents who are at risk for having a child with CAH.

The catalytic domain CysPc of the DEK1 calpain is functionally conserved in land plants.

DEK1, the single calpain of land plants, is a member of the ancient membrane bound TML-CysPc-C2L calpain family that dates back 1.5 billion years. Here we show that the CysPc-C2L domains of land plant calpains form a separate sub-clade in the DEK1 clade of the phylogenetic tree of plants. The charophycean alga Mesostigma viride DEK1-like gene is clearly divergent from those in land plants, suggesting that a major evolutionary shift in DEK1 occurred during the transition to land plants. Based on genetic complementation of the Arabidopsis thaliana dek1-3 mutant using CysPc-C2L domains of various origins, we show that these two domains have been functionally conserved within land plants for at least 450 million years. This conclusion is based on the observation that the CysPc-C2L domains of DEK1 from the moss Physcomitrella patens complements the A. thaliana dek1-3 mutant phenotype. In contrast, neither the CysPc-C2L domains from M. viride nor chimeric animal-plant calpains complement this mutant. Co-evolution analysis identified differences in the interactions between the CysPc-C2L residues of DEK1 and classical calpains, supporting the view that the two enzymes are regulated by fundamentally different mechanisms. Using the A. thaliana dek1-3 complementation assay, we show that four conserved amino acid residues of two Ca²âº-binding sites in the CysPc domain of classical calpains are conserved in land plants and functionally essential in A. thaliana DEK1.