Condition and size of the non‐native pikeperch Sander lucioperca (Linnaeus, 1758) in Portuguese river basins

We studied life‐history traits focusing on the growth and condition of the pikeperch Sander lucioperca to evaluate its phenotypic plasticity when introduced to new environments. Pikeperch is a non‐native fish introduced to Iberian freshwater fauna in 1998 that quickly spread to other river basins through human‐mediated activities, occupying now a wide variety of habitats along mainland Portugal. Condition (K and SMI), fork length at age, and length–weight relationships were studied for Portuguese populations. Pikeperch fork length for ages 1, 2, 3, and 4 was different between several populations. We applied generalized linear models (GLM) to study the influence of habitat type, latitude, altitude, time after first detection, and fish prey richness on pikeperch populations size at age 4 and condition. We observed higher condition values on populations from lower altitudes at lentic systems more recently introduced. But higher fork length at age 4 was found in populations from higher altitudes, on older populations with higher prey richness. Habitat type, time since first detection, and fish fauna composition are discussed as the main environmental factors explaining the observed phenotypic plasticity with concerns on predatory impact on native fauna.     

Improved search heuristics find 20 000 new alignments between human and mouse genomes

Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. By considering substitution patterns of real genomes, we design sets of multiple complementary transition seeds, which have better performance (sensitivity per run time) than previous seeding strategies. Often the best seed patterns have more transition positions than those used previously. We also point out that recent computer memory sizes (e.g. 60 GB) make it feasible to use multiple (e.g. eight) seeds for whole mammal genomes. Interestingly, the most sensitive settings achieve diminishing returns for human–dog and melanogaster–pseudoobscura comparisons, but not for human–mouse, which suggests that we still miss many human–mouse alignments. Our optimized heuristics find ∼20 000 new human–mouse alignments that are missing from the standard UCSC alignments. We tabulate seed patterns and parameters that work well so they can be used in future research.     

Requirements for human‐induced pluripotent stem cells

‘Requirements for Human‐Induced Pluripotent Stem Cells’ is the first set of guidelines on human‐induced pluripotent stem cells in China, jointly drafted and agreed upon by experts from the Chinese Society for Stem Cell Research. This standard specifies the technical requirements, test methods, and instructions for use, labeling, packaging, storage, transportation, and waste handling for human‐induced pluripotent stem cells, which apply to the production and quality control of human‐induced pluripotent stem cells. It was released by the Chinese Society for Cell Biology on 9 January 2021 and came into effect on 9 April 2021. We hope that the publication of these guidelines will promote institutional establishment, acceptance, and execution of proper protocols and accelerate the international standardization of human‐induced pluripotent stem cells for applications.     

Genomic relationships and speciation times of human, chimpanzee, and gorilla inferred from a coalescent hidden Markov model

The genealogical relationship of human, chimpanzee, and gorilla varies along the genome. We develop a hidden Markov model (HMM) that incorporates this variation and relate the model parameters to population genetics quantities such as speciation times and ancestral population sizes. Our HMM is an analytically tractable approximation to the coalescent process with recombination, and in simulations we see no apparent bias in the HMM estimates. We apply the HMM to four autosomal contiguous human–chimp–gorilla–orangutan alignments comprising a total of 1.9 million base pairs. We find a very recent speciation time of human–chimp (4.1 ± 0.4 million years), and fairly large ancestral effective population sizes (65,000 ± 30,000 for the human–chimp ancestor and 45,000 ± 10,000 for the human–chimp–gorilla ancestor). Furthermore, around 50% of the human genome coalesces with chimpanzee after speciation with gorilla. We also consider 250,000 base pairs of X-chromosome alignments and find an effective population size much smaller than 75% of the autosomal effective population sizes. Finally, we find that the rate of transitions between different genealogies correlates well with the region-wide present-day human recombination rate, but does not correlate with the fine-scale recombination rates and recombination hot spots, suggesting that the latter are evolutionarily transient.     

Robust Short-Term Memory without Synaptic Learning

Short-term memory in the brain cannot in general be explained the way long-term memory can – as a gradual modification of synaptic weights – since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.     

Complex networks and deep learning for EEG signal analysis

Electroencephalogram (EEG) signals acquired from brain can provide an effective representation of the human’s physiological and pathological states. Up to now, much work has been conducted to study and analyze the EEG signals, aiming at spying the current states or the evolution characteristics of the complex brain system. Considering the complex interactions between different structural and functional brain regions, brain network has received a lot of attention and has made great progress in brain mechanism research. In addition, characterized by autonomous, multi-layer and diversified feature extraction, deep learning has provided an effective and feasible solution for solving complex classification problems in many fields, including brain state research. Both of them show strong ability in EEG signal analysis, but the combination of these two theories to solve the difficult classification problems based on EEG signals is still in its infancy. We here review the application of these two theories in EEG signal research, mainly involving brain–computer interface, neurological disorders and cognitive analysis. Furthermore, we also develop a framework combining recurrence plots and convolutional neural network to achieve fatigue driving recognition. The results demonstrate that complex networks and deep learning can effectively implement functional complementarity for better feature extraction and classification, especially in EEG signal analysis.     

Genome-wide survey for biologically functional pseudogenes

According to current estimates there exist about 20,000 pseudogenes in a mammalian genome. The vast majority of these are disabled and nonfunctional copies of protein-coding genes which, therefore, evolve neutrally. Recent findings that a Makorin1 pseudogene, residing on mouse Chromosome 5, is, indeed, in vivo vital and also evolutionarily preserved, encouraged us to conduct a genome-wide survey for other functional pseudogenes in human, mouse, and chimpanzee. We identify to our knowledge the first examples of conserved pseudogenes common to human and mouse, originating from one duplication predating the human–mouse species split and having evolved as pseudogenes since the species split. Functionality is one possible way to explain the apparently contradictory properties of such pseudogene pairs, i.e., high conservation and ancient origin. The hypothesis of functionality is tested by comparing expression evidence and synteny of the candidates with proper test sets. The tests suggest potential biological function. Our candidate set includes a small set of long-lived pseudogenes whose unknown potential function is retained since before the human–mouse species split, and also a larger group of primate-specific ones found from human–chimpanzee searches. Two processed sequences are notable, their conservation since the human–mouse split being as high as most protein-coding genes; one is derived from the protein Ataxin 7-like 3 (ATX7NL3), and one from the Spinocerebellar ataxia type 1 protein (ATX1). Our approach is comparative and can be applied to any pair of species. It is implemented by a semi-automated pipeline based on cross-species BLAST comparisons and maximum-likelihood phylogeny estimations. To separate pseudogenes from protein-coding genes, we use standard methods, utilizing in-frame disablements, as well as a probabilistic filter based on Ka/Ks ratios.     

社会认知神经科学的取向与研究进展

社会认知神经科学是社会心理学和认知神经科学相结合的新兴多学科研究领域,其强调在社会、认知与脑神经等三个层面的交互作用上去理解心理现象。前几年主要是对刻板印象、态度与态度改变、他人知觉、自我认知以及情绪与认知交互作用等方面进行了深入研究,其主要范式是应用认知神经科学的方法来验证社会心理学在这些范围内上的各种不同的理论观点,当前的研究主要集中在知觉和再认的社会标记、社会判断和归因、评价调节知觉和经验以及社会交互作用等传统的社会心理学方面,并取得了突破性进展。展望未来的研究,其将在系统准则研究发展的基础上,把当今的社会认知研究与认知神经科学在理论和方法论上整合起来,为揭示人类高级社会心理现象的神经基础,开辟一条崭新的研究道路。     

The legacy of Donald O. Hebb: more than the Hebb synapse

Neuroscientists associate the name of Donald O. Hebb with the Hebbian synapse and the Hebbian learning rule, which underlie connectionist theories and synaptic plasticity, but Hebb's work has also influenced developmental psychology, neuropsychology, perception and the study of emotions, as well as learning and memory. Here, we review the work of Hebb and its lasting influence on neuroscience in honour of the 2004 centenary of his birth.     

The Mind-Writing Pupil: A Human-Computer Interface Based on Decoding of Covert Attention through Pupillometry

We present a new human-computer interface that is based on decoding of attention through pupillometry. Our method builds on the recent finding that covert visual attention affects the pupillary light response: Your pupil constricts when you covertly (without looking at it) attend to a bright, compared to a dark, stimulus. In our method, participants covertly attend to one of several letters with oscillating brightness. Pupil size reflects the brightness of the selected letter, which allows us–with high accuracy and in real time–to determine which letter the participant intends to select. The performance of our method is comparable to the best covert-attention brain-computer interfaces to date, and has several advantages: no movement other than pupil-size change is required; no physical contact is required (i.e. no electrodes); it is easy to use; and it is reliable. Potential applications include: communication with totally locked-in patients, training of sustained attention, and ultra-secure password input.     

Activity: Structure,Genesis, and Unit of Analysis

One of the most notable phenomena in Soviet psychology since the late '70s has been discussion of the relationship between communication and activity [8,13,18,19,21,23]. I consider the following formulation of the problem, given here in its most general form, the most constructive: communication and activity are indubitably interrelated, but communication (in contrast to perception, memory, etc.) cannot, in any constructive way, be regarded as a type of activity and analyzed within the framework of Leont 'ev's paradigm (activity—action—operation; motive—goal—condition). This formulation of the problem is useful primarily in terms of the further progress of the theory of activity: it quite incisively focuses on one essential point that has been inadequately dealt with in the theory of activity, namely, an analysis of the social means and mechanisms of human activity, both collective and individual.     

What electrical microstimulation has revealed about the neural basis of cognition

Neurophysiologists have shown repeatedly that neural activity in different brain structures can be correlated with specific perceptual and cognitive functions, but the causal efficacy of the observed activity has generally been a matter of conjecture. By contrast, electrical microstimulation, which allows the experimenter to manipulate the activity of small groups of neurons with spatial and temporal precision, can now be used to demonstrate causal links between neural activity and specific cognitive functions. Here, we review this growing literature, including applications to the study of attention, visual and somatosensory perception, 'read-out' mechanisms for interpreting sensory maps, and contextual effects on perception. We also discuss potential applications of microstimulation to studies of higher cognitive functions such as decision-making and subjective experience.     

What failure in collective decision-making tells us about metacognition

Condorcet (1785) proposed that a majority vote drawn from individual, independent and fallible (but not totally uninformed) opinions provides near-perfect accuracy if the number of voters is adequately large. Research in social psychology has since then repeatedly demonstrated that collectives can and do fail more often than expected by Condorcet. Since human collective decisions often follow from exchange of opinions, these failures provide an exquisite opportunity to understand human communication of metacognitive confidence. This question can be addressed by recasting collective decision-making as an information-integration problem similar to multisensory (cross-modal) perception. Previous research in systems neuroscience shows that one brain can integrate information from multiple senses nearly optimally. Inverting the question, we ask: under what conditions can two brains integrate information about one sensory modality optimally? We review recent work that has taken this approach and report discoveries about the quantitative limits of collective perceptual decision-making, and the role of the mode of communication and feedback in collective decision-making. We propose that shared metacognitive confidence conveys the strength of an individual's opinion and its reliability inseparably. We further suggest that a functional role of shared metacognition is to provide substitute signals in situations where outcome is necessary for learning but unavailable or impossible to establish.     

The amygdala and reward

The amygdala -- an almond-shaped group of nuclei at the heart of the telencephalon -- has been associated with a range of cognitive functions, including emotion, learning, memory, attention and perception. Most current views of amygdala function emphasize its role in negative emotions, such as fear, and in linking negative emotions with other aspects of cognition, such as learning and memory. However, recent evidence supports a role for the amygdala in processing positive emotions as well as negative ones, including learning about the beneficial biological value of stimuli. Indeed, the amygdala's role in stimulus-reward learning might be just as important as its role in processing negative affect and fear conditioning.     

Feature Selection for Speech Emotion Recognition in Spanish and Basque: On the Use of Machine Learning to Improve Human-Computer Interaction

Study of emotions in human–computer interaction is a growing research area. This paper shows an attempt to select the most significant features for emotion recognition in spoken Basque and Spanish Languages using different methods for feature selection. RekEmozio database was used as the experimental data set. Several Machine Learning paradigms were used for the emotion classification task. Experiments were executed in three phases, using different sets of features as classification variables in each phase. Moreover, feature subset selection was applied at each phase in order to seek for the most relevant feature subset. The three phases approach was selected to check the validity of the proposed approach. Achieved results show that an instance-based learning algorithm using feature subset selection techniques based on evolutionary algorithms is the best Machine Learning paradigm in automatic emotion recognition, with all different feature sets, obtaining a mean of 80,05% emotion recognition rate in Basque and a 74,82% in Spanish. In order to check the goodness of the proposed process, a greedy searching approach (FSS-Forward) has been applied and a comparison between them is provided. Based on achieved results, a set of most relevant non-speaker dependent features is proposed for both languages and new perspectives are suggested.     

MM-MDS: A Multidimensional Scaling Database with Similarity Ratings for 240 Object Categories from the Massive Memory Picture Database

Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of “sameness” among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory. Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category. In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16–17 exemplar objects. We collected similarity ratings using the spatial arrangement method. Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications. For each picture, we categorized the item''s prototypicality, indexed by its proximity to other items in the space. We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space. These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of “sameness.”     

Canada geese (Branta canadensis) nesting on elevated structures in urban Indiana,USA

The Canada goose (Branta canadensis) population has radically changed over the past 60 years—from once being extirpated in the state of Indiana to the current level of approximately 113,000. High urban densities have resulted in persistent human–wildlife conflicts and novel interactions between geese and their physical environment. Canada geese typically choose nest sites that are on the ground or slightly elevated sites such as muskrat lodge, but we report observations of Canada geese nesting on rooftops 2.6–12.2 m above ground level in central Indiana. These observations suggest that alternative, unpredicted nesting sites are being chosen over more traditional sites, in a likely attempt to reduce risks of disturbance and predation. This atypical nest‐site selection may pose new management challenges, but further research is needed.     

Understanding self and others: from origins to disorders

In order to interpret and engage with the social world, individuals must understand how they relate to others. Self–other understanding forms the backbone of social cognition and is a central concept explored by research into basic processes such as action perception and empathy, as well as research on more sophisticated social behaviours such as cooperation and intergroup interaction. This theme issue integrates the latest research into self–other understanding from evolutionary biology, anthropology, psychology, neuroscience and psychiatry. By gathering perspectives from a diverse range of disciplines, the contributions showcase ways in which research in these areas both informs and is informed by approaches spanning the biological and social sciences, thus deepening our understanding of how we relate to others in a social world.     

脑机融合系统综述

脑机接口是生物脑与电脑或机器之间的一种直接连接通路。脑机融合计算系统是一种基于脑机接口技术,综合利用生物智能和机器智能的新型智能融合系统,其在医疗康复、生活娱乐和军事侦查等方面具有巨大的应用开发潜力。首先从信息传输的角度简述由脑机接口到脑机融合的发展趋势;其次重点阐述脑机融合系统的概念及其研究所面临的挑战,并分三个层次介绍当前若干典型相关工作;最后介绍吴朝晖课题组在脑机融合计算系统方面的相关工作。     

Human Papillomavirus (HPV) Vaccination and Adolescent Girls' Knowledge and Sexuality in Western Uganda: A Comparative Cross-Sectional Study

The purpose of the study was to investigate the influence of human papillomavirus (HPV) vaccination on adolescent girls’ knowledge of HPV and HPV vaccine, perception of sexual risk and intentions for sexual debut. This cross-sectional comparative study was conducted in Ibanda and Mbarara districts. Data was collected using a standardized self-administered questionnaire and analyzed using the Statistical Package for the Social Sciences computer software. Univariate, bivariate, and logistic regression analyses were conducted with significance level set at p < .05. Results showed that HPV vaccination was associated with being knowledgeable (Crude OR: 5.26, CI: 2.32–11.93; p = 0.000). Vaccination against HPV did not predict perception of sexual risk. Knowledge was low (only 87/385 or 22.6% of vaccinated girls were knowledgeable), but predicted perception of a high sexual risk (Adjusted OR: 3.12, CI: 1.37–3.63; p = 0.008). HPV vaccination, knowledge and perceived sexual risk did not predict sexual behaviour intentions. High parental communication was associated with adolescent attitudes that support postponement of sexual debut in both bivariate and multiple regression analyses. In conclusion, findings of this study suggest that HPV vaccination is not likely to encourage adolescent sexual activity. Influence of knowledge on sexual behaviour intentions was not definitively explained. Prospective cohort studies were proposed to address the emerging questions.