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The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN) model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP) with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP) and synaptic normalization (SN). When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network’s changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network’s sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that STDP, IP, and SN may be the driving forces behind our ability to learn complex action sequences.
Infants' poor motor abilities limit their interaction with their environment and render studying infant cognition notoriously difficult. Exceptions are eye movements, which reach high accuracy early, but generally do not allow manipulation of the physical environment. In this study, real-time eye tracking is used to put 6- and 8-month-old infants in direct control of their visual surroundings to study the fundamental problem of discovery of agency, i.e. the ability to infer that certain sensory events are caused by one's own actions. We demonstrate that infants quickly learn to perform eye movements to trigger the appearance of new stimuli and that they anticipate the consequences of their actions in as few as 3 trials. Our findings show that infants can rapidly discover new ways of controlling their environment. We suggest that gaze-contingent paradigms offer effective new ways for studying many aspects of infant learning and cognition in an interactive fashion and provide new opportunities for behavioral training and treatment in infants.
Spherical harmonics coeffcients for ligand-based virtual screening of cyclooxygenase inhibitors
(2011)
Background: Molecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening. Methodology/Principal Findings: We introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization. Conclusions/Significance: 12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort.
In our daily life, we carry out lots of tasks like typing, playing tennis, and playing the piano, without even noticing there is sequence learning involved. No matter how simple or complex they are, these tasks require the sequential planning and execution of a series of movements. As an ability of primary importance in one’s life, and an ability that everyone manages to learn, action-sequence learning has been studied by researchers from different fields: psychologists, neurophysiologists as well as roboticists. In the concept of sequence learning, perceptual learning and motor learning, implicit and explicit learning have been studied and discussed independently.
We are interested in infancy research, because infants, with underdeveloped brain functions and with limited motor ability, have little experience with the world and not yet built internal models as presumption of how to interpret the world. A series of infant experiments in the 1980s provided evidence that infants can rapidly develop anticipatory eye movements for visual events. Even when infants have no control of those spatial-temporal patterns, they can respond actually prior to the onset of the visual event, referred as "Anticipation".
In this work, we applied a gaze-contingent paradigm using real-time eye tracking to put 6- and 8-month-old infants in direct control of their visual surroundings. This paradigm allows the infant to change an image on a screen by looking at a peripheral red disc, which functions as a switch. We found that infants quickly learn to perform eye movements to trigger the appearance of new stimuli and that they anticipate the consequences of their actions in an early stage of the experiment.
Attention-shift from learning one stimulus to the next novel stimulus is important in sequence learning. In the test phase of infant visual habituation with two objects, we propose a new theory of explaining the familiarity-to-novelty shift. In our opinion an infant’s interest in a stimulus is related to its learning progress, the improvement of performance. As a consequence, infants prefer the stimulus which their current learning progress is maximal for, naturally giving rise to a familiarity-to-novelty shift in certain situations. Our network model predicts that the familiarity-to-novelty-shift only emerges for complex stimuli that produce bell-shaped learning curves after brief familiarization, but does not emerge for simple stimuli that produce exponentially decreasing learning curves or for long familiarization time, which is consistent with experimental results. This research suggests the infant's interest in a stimulus may be related to its current learning progress. This can give rise to a dynamic familiarity-to-novelty shift depending on both the infant's learning efficiency and the task complexity.
We know that for both infants and adults, the performance on certain motor-sequence tasks can be improved through practice. However, adults usually have to perform complex tasks in complicated environments; for example, learning multiple tasks is unavoidable in our daily life. In existing research, learning multiple tasks showed puzzling and seemingly contradictory results. On the one hand, a wide variety of proactive and retroactive interference effects have been observed when multiple tasks have to be learned. On the other hand, some studies have reported facilitation and transfer of learning between different tasks.
In order to find out the interaction between multiple-task learning, and to find an optimal training schedule, we use a recurrent neural network to model a series of experiments on movement sequence learning. The network model learns to carry out the correct movement sequences through training and reproduces differences between training schedules such as blocked training vs. random training in psychophysics experiments. The network model also shows striking similarity to human performance, and makes prediction for tasks similarity and different training schedules.
In conclusion, the thesis presents learning sequences of actions in infants and recurrent neural networks. We carried out a gaze-contingent experiment to study infants’ rapid anticipation of their own action outcomes, and we also constructed two recurrent neural network models, with one model explaining infant attention shift in visual habituation, and the other model directing to task similarity and training schedule in motor sequence control in adults.
The Chinese species of the genus Chinoperla Zwick, 1980 are reviewed. One species from Hainan is described as new to science: C. changjiangensis sp. nov. Chinoperla gorohovi Sivec & Stark, 2010 is reported from China for the first time, with a redescripion and color images of the male, and the first description of the female and egg. Chinoperla nigrifrons (Banks, 1939) is redescribed and illustrated, synonymy of C. furcomacula (Wu, 1973) is confirmed. Taxonomic relationships within the studied species are discussed. A provisional key to the six known species of Chinoperla for China is presented.
Using a data sample of e+e− collision data corresponding to an integrated luminosity of 2.93 fb−1 collected with the BESIII detector at a center-of-mass energy of s=3.773GeV, we search for the singly Cabibbo-suppressed decays D0→π0π0π0, π0π0η, π0ηη and ηηη using the double tag method. The absolute branching fractions are measured to be B(D0→π0π0π0)=(2.0±0.4±0.3)×10−4, B(D0→π0π0η)=(3.8±1.1±0.7)×10−4 and B(D0→π0ηη)=(7.3±1.6±1.5)×10−4 with the statistical significances of 4.8σ, 3.8σ and 5.5σ, respectively, where the first uncertainties are statistical and the second ones systematic. No significant signal of D0→ηηη is found, and the upper limit on its decay branching fraction is set to be B(D0→ηηη)<1.3×10−4 at the 90% confidence level.
By analyzing 6.32 fb − 1 of e+ e− annihilation data collected at the center-of-mass energies between 4.178 and 4.226 GeV with the BESIII detector, we determine the branching fraction of the leptonic decay D + s → τ + ντ, with τ+ → π + π0¯ντ, to be B D + s → τ + ν τ = (5.29 ± 0.25 stat ± 0.20 syst) %. We estimate the product of the Cabibbo-Kobayashi-Maskawa matrix element |Vcs|and the D + s decay constant f D + s to be f D + s|Vcs| = (244.8 ± 5.8 stat ± 4.8syst) MeV, using the known values of the τ + and D + s masses as well as the D + s lifetime, together with our branching fraction measurement. Combining the value of |Vcs| obtained from a global fit in the standard model and f D + s from lattice quantum chromodynamics, we obtain f D + s = (251.6 ± 5.9 stat ± 4.9syst) MeV and |Vcs| = 0.980 ± 0.023 stat ± 0.019 syst. Using the branching fraction of B D + s → μ + νμ = (5.35±0.21)×10−3, we obtain the ratio of the branching fractions B D + s → τ + ντ/B D +s → μ+νμ = 9.89±0.71, which is consistent with the standard model prediction of lepton flavor universality.
We report a measurement of the observed cross sections of e+ e− → J/ψX based on 3.21 fb − 1 of data accumulated at energies from 3.645 to 3.891 GeV with the BESIII detector operated at the BEPCII collider. In analysis of the cross sections, we measured the decay branching fractions of B(ψ(3686) → J/ψX) = (64.4 ± 0.6 ± 1.6)% and B(ψ(3770) → J/ψX) = (0.5 ± 0.2 ± 0.1)% for the first time. The energy-dependent line shape of these cross sections cannot be well described by two Breit-Wigner (BW) amplitudes of the expected decays ψ (3686) → J/ψX and ψ(3770) → J/ψX. Instead, it can be better described with one more BW amplitude of the decay R(3760)→ J/ψX. Under this assumption, we extracted the R (3760) mass M R (3760 ) = 3766.2 ± 3.8 ± 0.4 MeV/c2, total width Γ tot R ( 3760 ) = 22.2 ± 5.9 ± 1.4 MeV, and product of leptonic width and decay branching fraction
ΓeeR(3760) B[R(3760) → J/ψX] = (79.4 ± 85.5 ± 11.7) eV. The significance of the R(3760) is 5.3σ. The first uncertainties of these measured quantities are from fits to the cross sections and second systematic.
The process e+e−→ϕη is studied at 22 center-of-mass energy points (√s) between 2.00 and 3.08 GeV using 715 pb−1 of data collected with the BESIII detector. The measured Born cross section of e+e−→ϕη is found to be consistent with BABAR measurements, but with improved precision. A resonant structure around 2.175 GeV is observed with a significance of 6.9σ with mass (2163.5±6.2±3.0) MeV/c2 and width (31.1+21.1−11.6±1.1) MeV, where the first uncertainties are statistical and the second are systematic.
The electromagnetic process is studied with the initial-state-radiation technique using 7.5 fb−1 of data collected by the BESIII experiment at seven energy points from 3.773 to 4.600 GeV. The Born cross section and the effective form factor of the proton are measured from the production threshold to 3.0 GeV/ using the invariant-mass spectrum. The ratio of electric and magnetic form factors of the proton is determined from the analysis of the proton-helicity angular distribution.