PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Predictive Learning Models”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59Linked to original sources
PubMed2004

Enhancing active learning in the student laboratory.

We previously examined how three approaches to directing students in a laboratory setting impacted their ability to repair a faulty mental model in respiratory physiology (Modell, HI, Michael JA, Adamson T, Goldberg J, Horwitz BA, Bruce DS, Hudson ML, Whitescarver SA, and Williams S. Adv Physiol Educ 23: 82-90, 2000). This study addresses issues raised by the results of that work. In one group, a written protocol directed students to predict what would happen to frequency and depth of breathing during exercise on a bicycle ergometer, run the experiment, and compare their results to their predictions ("predictor without verification"). In a "predictor with verification" group, students followed the same written protocol but were also required to show the instructor their predictions before running the experiment. Students in a third group reported their predictions verbally to an instructor immediately before exercise and reviewed their results with that instructor immediately after exercise ("instructor intervention group"). Results of this study were consistent with our earlier work. The predictor with verification and predictor without verification protocols yielded similar results. The instructor intervention protocol yielded higher success rates in repairing students' mental models. We subsequently assessed the efficacy of a prediction period at the beginning of the lab session and a wrap-up period at the end to compare predictions and results. This predict and wrap-up protocol was more effective than the predictor without verification protocol, but it was not as effective as the instructor intervention protocol. Although these results may reflect multiple factors impacting learning in the student laboratory, we believe that a major factor is a mismatch between students' approaches to learning and the intended learning outcomes of the experience.

Education, Medical, Undergraduate↗
PubMed2002

Simulating closed- and open-loop voluntary movement: a nonlinear control-systems approach.

In many recent human motor control models, including feedback-error learning and adaptive model theory (AMT), feedback control is used to correct errors while an inverse model is simultaneously tuned to provide accurate feedforward control. This popular and appealing hypothesis, based on a combination of psychophysical observations and engineering considerations, predicts that once the tuning of the inverse model is complete the role of feedback control is limited to the correction of disturbances. This hypothesis was tested by looking at the open-loop behavior of the human motor system during adaptation. An experiment was carried out involving 20 normal adult subjects who learned a novel visuomotor relationship on a pursuit tracking task with a steering wheel for input. During learning, the response cursor was periodically blanked, removing all feedback about the external system (i.e., about the relationship between hand motion and response cursor motion). Open-loop behavior was not consistent with a progressive transfer from closed- to open-loop control. Our recently developed computational model of the brain--a novel nonlinear implementation of AMT--was able to reproduce the observed closed- and open-loop results. In contrast, other control-systems models exhibited only minimal feedback control following adaptation, leading to incorrect open-loop behavior. This is because our model continues to use feedback to control slow movements after adaptation is complete. This behavior enhances the internal stability of the inverse model. In summary, our computational model is currently the only motor control model able to accurately simulate the closed- and open-loop characteristics of the experimental response trajectories.

Adaptation, Biological↗
PubMedDate not supplied

Implicit and explicit memory in amnesia: some explanations and predictions by the TraceLink model.

After a brief overview of some of the characteristics and neuroanatomy of amnesia, a new model of amnesia is described: the TraceLink model. One novel aspect of the model is that it makes specific and testable predictions regarding semantic dementia, a recently described disorder that is viewed here as being related to amnesia. The TraceLink model consists of: a trace system (roughly the neocortix), a link system (hippocampus and adjacent areas), and a modulatory system (certain basal forebrain nuclei). Different forms of learning in the TraceLink model are explained, followed by a discussion of implicit and explicit memory, prominence (ease of recall) and persistence (resistance to brain damage), consolidation, and Ribot gradients in retrograde amnesia. Patterns of recovery from retrograde amnesia are also discussed, and novel predictions are derived regarding implicit memory and various forms of amnesia.

Amnesia↗
PubMedDate not supplied

Culture models for the study of estradiol-induced synaptic plasticity.

Estrogen, which classically affects areas of the brain related to reproduction, has also been found to affect brain regions important in learning and memory. Additionally, it has been suggested that estrogen exerts protective effects against neurodegenerative diseases such as Alzheimer's disease. Important mechanisms by which estrogen may confer protection are through the maintenance or modulation of existing synapses, or by the production of new ones. It has now been demonstrated that estrogen can increase synaptogenesis and spine production in the hippocampus, both in vivo as well as in primary hippocampal neurons in culture. The latter model system is the primary focus of this review. Synaptogenesis and spine production have been well characterized in developing and adult animals, and parallels between the synaptic morphology reflecting these processes can be readily observed in high-density primary hippocampal cultures. Moreover, in culture, estrogen induces a variety of ultrastructural modifications, many of which occur in vivo, that have been linked to various in vivo models of learning and memory. For these reasons, high-density hippocampal culture systems should be regarded as valuable tools with which to predict in vivo physiology, and may well be particularly useful for studies of the neuroprotective effects of estrogen.

Animals↗
PubMed2003

The association between student characteristics and the development of clinical reasoning in a graduate-entry, PBL medical programme.

This study sought to assess the extent to which the entry characteristics of students in a graduate-entry medical programme predict the subsequent development of clinical reasoning ability. Subjects comprised 290 students voluntarily recruited from three successive cohorts of the University of Queensland's MBBS Programme. Clinical reasoning was measured once a year over a period of three years using two methods, a set of 10 Clinical Reasoning Problems (CRPs) and the Diagnostic Thinking Inventory (DTI). Data on gender, age at entry into the programme, nature of primary degree, scores on selection criteria (written examination plus interview) and academic performance in the first two years of the programme were recorded for each student, and their association with clinical reasoning skill analysed using univariate and multivariate analysis. Univariate analysis indicated significant associations between CRP score, gender and primary degree with a significant but small association between DTI and interview score. Stage of progression through the programme was also an important predictor of performance on both indicators. Subsequent multivariate analysis suggested that female gender is a positive predictor of CRP score independently of the nature of a subject's primary degree and stage of progression through the programme, although these latter two variables are interdependent. Positive predictors of clinical reasoning skill are stage of progression through the MBBS programme, female gender and interview score. Although the nature of a student's primary degree is important in the early years of the programme, evidence suggests that by graduation differences between students' clinical reasoning skill due to this factor have been resolved.

Adolescent↗
PubMed1994

Psychological expectancy as mediator of vulnerability to alcoholism.

Alcohol expectancy has proven to be a powerful predictor of drinking behavior, including alcoholism, in a wide range of groups. Three recent studies that begin to address expectancy's relation to other alcoholism vulnerability factors are reviewed. Results indicate that: (1) expectancies for reinforcement from alcohol predate teens' first drinking experiences; (2) expectancies predict subsequent drinking onset and problem drinking; (3) high initial expectancies lead to a vicious cycle of progressively more drinking and more positive expectancies during the adolescent years; (4) expectancy mediates the influence of family drinking history on adolescent drinking; and (5) as an alcohol-specific risk factor, expectancy adds to and (in women) interacts with more general, dispositional (personality) risk factors to predict problem drinking in young adults. These findings support the model of expectancy as a mediator of the original causal influences of earlier learning experiences.

Adolescent↗
PubMed2001

Ability in perceiving nonnative contrasts: performance on natural and synthetic speech stimuli.

The perception of the distinction between /r/ and /l/ by native speakers of American English and of Japanese was studied using natural and synthetic speech. The American subjects were all nearly perfect at recognizing the natural speech sounds, whereas there was substantial variation among the Japanese subjects in their accuracy of recognizing /r/ and /l/ except in syllable-final position. A logit model, which additively combined the acoustic information conveyed by F1-transition duration and by F3-onset frequency, provided a good fit to the perception of synthetic /r/ and /l/ by the American subjects. There was substantial variation among the Japanese subjects in whether the F1 and F3 cues had a significant effect on their classifications of the synthetic speech. This variation was related to variation in accuracy of recognizing natural /r/ and /l/, such that greater use of both the F1 cue and the F3 cue in classifying the synthetic speech sounds was positively related to accuracy in recognizing the natural sounds. However, multiple regression showed that use of the F1 cue did not account for significant variance in natural speech performance beyond that accounted for by the F3 cue, indicating that the F3 cue is more important than the F1 cue for Japanese speakers learning English. The relation between performance on natural and synthetic speech also provides external validation of the logit model by showing that it predicts performance outside of the domain of data to which it was fit.

Adult↗
PubMed2002

Distinguishing prototype-based and exemplar-based processes in dot-pattern category learning.

The authors contrast exemplar-based and prototype-based processes in dot-pattern categorization. In Experiments 1A and 1B, participants provided similarity ratings of dot-distortion pairs that were distortions of the same originating prototype. The results show that comparisons to training exemplars surrounding the prototype create flat typicality gradients within a category and small prototype-enhancement effects, whereas comparisons to a prototype center create steep typicality gradients within a category and large prototype-enhancement effects. Thus, prototype and exemplar theories make different predictions regarding common versions of the dot-distortion task. Experiment 2 tested these different predictions by having participants learn dot-pattern categories. The steep typicality gradients, the large prototype effects, and the superior fit of prototype models suggest that participants refer to-be-categorized items to a representation near the category's center (the prototype), and not to the training exemplars that surround the prototype.

Attention↗
PubMed2026

Data distribution impacts the performance and generalisability of contrastive learning-based foundation models of electrocardiograms.

Contrastive learning is a widely adopted self-supervised pretraining strategy, yet its dependence on cohort composition remains underexplored. We present Contrasting by Augmented Patient Electrocardiograms (CAPE) foundation model and pretrain on four cohorts (n = 5,203,269), from diverse populations across three continents (North America, South America, Asia). We systematically assess how cohort demographics, health status, and population diversity influence the downstream performance for prediction tasks also including two additional cohorts from another continent (Europe). We find that downstream performance depends on the distributional properties of the pretraining cohort, including demographics and health status. Moreover, while pretraining with a multi-centre, demographically diverse cohort improves in-distribution accuracy, it reduces out-of-distribution (OOD) generalisation of our contrastive approach by encoding cohort-specific artifacts. To address this, we propose the In-Distribution Batch (IDB) strategy, which preserves intra-cohort consistency during pretraining, discourages learning of spurious cohort-specific features, and instead promotes clinically meaningful variability within cohorts. This leads to improved out-of-distribution robustness, with gains of 9-40% in downstream label prediction performance. This work provides insights into pretraining strategies for more clinically deployable and generalisable foundation models.

Journal Article↗
PubMed2004

Testing a social psychological model of strategy use with students of english as a foreign language.

This replication study tested MacIntyre's Social Psychological Model of Strategy Use. Participants were 137 first-year college students (100 men and 37 women), all in their late teens or early 20s, learning English as a foreign language in a university in Taiwan. McIntyre specified three conditions for use of language-learning strategies in his model: awareness of the strategy, having a reason to use it, and not having a reason not to use it. Stepwise multiple regression analyses of data measured by Oxford's 50-item Strategy Inventory for Language Learning partially support this model because only Knowledge about the Strategy (representing the first condition) and Difficulty about Using It (representing the third condition) made significant independent contributions to the prediction of use of most of the 50 strategies. Close examination of the results poses questions about MacIntyre and Noels' thesis, as implied in their revised model, that reason to use the strategy and reason not to use the strategy are independent. The present replication suggests a need for further revision of the model. Use of methods more advanced than the multiple regression is recommended to test and refine the model.

Adolescent↗
PubMedDate not supplied

Is English a dyslexic language?

McGuinness has suggested that there 'is no diagnosis and no evidence for any special type of reading disorder like dyslexia', and that poor teaching accounts for low levels of English literacy performance, rather than inherent personal deficits. Implicit in this is the assumption that some languages have simple grapheme-phoneme codes in which there is a one-to-one mapping, making them easy to teach and learn, while others have more complicated structures and are more difficult for teachers and students. There is now an increasing number of studies which demonstrate that readers in more transparent orthographies such as Italian, Spanish, Turkish, Greek and German have little difficulty in decoding written words, while English children have many more problems. Increasingly, lack of orthographic transparency in English is seen as having a powerful negative effect on the development of reading skills in English-speaking children. There is evidence that English-speaking children who fail to acquire reading skills may fall into two distinct categories: those who would succeed in languages, other than English, that have greater orthographic consistency; and those who would still have problems even with perfect orthographic transparency. The first, larger, group is let down by the interaction of poor teaching methods and an incomprehensible system of orthography. The present study examines word factors associated with poor spelling and reading that have been identified. Three factors account for the relative ease with which pupils can spell words: frequency of the word in the English language; length of the word; and the presence of 'tricky' letters or letter combinations. Data are presented illustrating the predictive model of spelling and reading which enables word difficulty to be calculated from the characteristics of English words. The implications the model has for teaching and learning English are elaborated, with reference to the possible benefits to be derived from mother-tongue teaching in British schools.

Dyslexia↗
PubMed2026

Biological Parts in Yeast Synthetic Biology: From Regulatory Elements to Predictive Design Platforms.

Yeasts, particularly Saccharomyces cerevisiae, are important eukaryotic chassis for synthetic biology because of their tractable genetics, versatile toolkits, and broad utility in metabolic engineering and functional genomics. Progress in this field has been driven by biological parts that enable programmable control of gene expression and cellular behavior. Early efforts focused mainly on promoters, terminators, and other regulatory elements for tuning individual genes. However, as engineering expanded to multigene pathways, genetic circuits, and dynamic regulatory systems, the limits of part-centric design became clear. Part performance is often shaped by genomic context, chromatin state, host physiology, and interactions with other components, which restricts modularity and predictability. In response, yeast synthetic biology is shifting toward integrated design frameworks combining multilayer regulation, standardized assembly, automated experimentation, and computational modeling. This review provides an integrated perspective on the evolution of biological parts across DNA-, RNA-, and protein-level regulation, connecting these advances with assembly frameworks, biofoundries, and machine learning to trace the trajectory from part-centric engineering toward predictive, system-level design in yeast synthetic biology.

Biofoundry↗
PubMed2023

Inferring Metabolic States from Single Cell Transcriptomic Data via Geometric Deep Learning.

The ability to measure gene expression at single-cell resolution has elevated our understanding of how biological features emerge from complex and interdependent networks at molecular, cellular, and tissue scales. As technologies have evolved that complement scRNAseq measurements with things like single-cell proteomic, epigenomic, and genomic information, it becomes increasingly apparent how much biology exists as a product of multimodal regulation. Biological processes such as transcription, translation, and post-translational or epigenetic modification impose both energetic and specific molecular demands on a cell and are therefore implicitly constrained by the metabolic state of the cell. While metabolomics is crucial for defining a holistic model of any biological process, the chemical heterogeneity of the metabolome makes it particularly difficult to measure, and technologies capable of doing this at single-cell resolution are far behind other multiomics modalities. To address these challenges, we present GEFMAP (Gene Expression-based Flux Mapping and Metabolic Pathway Prediction), a method based on geometric deep learning for predicting flux through reactions in a global metabolic network using transcriptomics data, which we ultimately apply to scRNAseq. GEFMAP leverages the natural graph structure of metabolic networks to learn both a biological objective for each cell and estimate a mass-balanced relative flux rate for each reaction in each cell using novel deep learning models.

Preprint↗
PubMed2006

Early development of language by hand: composing, reading, listening, and speaking connections; three letter-writing modes; and fast mapping in spelling.

The first findings from a 5-year, overlapping-cohorts longitudinal study of typical language development are reported for (a) the interrelationships among Language by Ear (listening), Mouth (speaking), Eye (reading), and Hand (writing) in Cohort 1 in 1st and 3rd grade and Cohort 2 in 3rd and 5th grade; (b) the interrelationships among three modes of Language by Hand (writing manuscript letters with pen and keyboard and cursive letters with pen) in each cohort in the same grade levels as (a); and (c) the ability of the 1st graders in Cohort 1 and the 3rd graders in Cohort 2 to apply fast mapping in learning to spell pseudowords. Results showed that individual differences in Listening Comprehension, Oral Expression, Reading Comprehension, and Written Expression are stable developmentally, but each functional language system is only moderately correlated with the others. Likewise, manuscript writing, cursive writing, and keyboarding are only moderately correlated, and each has a different set of unique neuropsychological predictors depending on outcome measure and grade level. Results support the use of the following neuropsychological measures in assessing handwriting modes: orthographic coding, rapid automatic naming, finger succession (grapho-motor planning for sequential finger movements), inhibition, inhibition/switching, and phonemes skills (which may facilitate transfer of abstract letter identities across letter formats and modes of production). Both 1st and 3rd graders showed evidence of fast mapping of novel spoken word forms onto written word forms over 3 brief sessions (2 of which involved teaching) embedded in the assessment battery; and this fast mapping explained unique variance in their spelling achievement over and beyond their orthographic and phonological coding abilities and correlated significantly with current and next-year spelling achievement.

Age Factors↗
PubMed2005

A theory of cortical responses.

This article concerns the nature of evoked brain responses and the principles underlying their generation. We start with the premise that the sensory brain has evolved to represent or infer the causes of changes in its sensory inputs. The problem of inference is well formulated in statistical terms. The statistical fundaments of inference may therefore afford important constraints on neuronal implementation. By formulating the original ideas of Helmholtz on perception, in terms of modern-day statistical theories, one arrives at a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts.It turns out that the problems of inferring the causes of sensory input (perceptual inference) and learning the relationship between input and cause (perceptual learning) can be resolved using exactly the same principle. Specifically, both inference and learning rest on minimizing the brain's free energy, as defined in statistical physics. Furthermore, inference and learning can proceed in a biologically plausible fashion. Cortical responses can be seen as the brain's attempt to minimize the free energy induced by a stimulus and thereby encode the most likely cause of that stimulus. Similarly, learning emerges from changes in synaptic efficacy that minimize the free energy, averaged over all stimuli encountered. The underlying scheme rests on empirical Bayes and hierarchical models of how sensory input is caused. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of cortical organization and responses. The aim of this article is to encompass many apparently unrelated anatomical, physiological and psychophysical attributes of the brain within a single theoretical perspective. In terms of cortical architectures, the theoretical treatment predicts that sensory cortex should be arranged hierarchically, that connections should be reciprocal and that forward and backward connections should show a functional asymmetry (forward connections are driving, whereas backward connections are both driving and modulatory). In terms of synaptic physiology, it predicts associative plasticity and, for dynamic models, spike-timing-dependent plasticity. In terms of electrophysiology, it accounts for classical and extra classical receptive field effects and long-latency or endogenous components of evoked cortical responses. It predicts the attenuation of responses encoding prediction error with perceptual learning and explains many phenomena such as repetition suppression, mismatch negativity (MMN) and the P300 in electroencephalography. In psychophysical terms, it accounts for the behavioural correlates of these physiological phenomena, for example, priming and global precedence. The final focus of this article is on perceptual learning as measured with the MMN and the implications for empirical studies of coupling among cortical areas using evoked sensory responses.

Biophysical Phenomena↗
PubMed2002

Antidepressant-like activity of VN2222, a serotonin reuptake inhibitor with high affinity at 5-HT1A receptors.

It has been suggested that drugs combining serotonin (5-hydroxytryptamine, 5-HT) transporter blockade and 5-HT1A autoreceptor antagonism could be a novel strategy for a shorter onset of action and higher therapeutic efficacy of antidepressants. The present study was aimed at characterizing the pharmacology of 1-(3-benzo[b]tiophenyl)-3-[4-(2-methoxyphenyl)-1-piperazinyl]-1-propanol (VN2222) a new synthetic compound with high affinity at both the 5-HT transporter and 5-HT1A receptors and devoid of high affinity at other receptors studied, with the only exception of alpha1-adrenoceptors. In keeping with the binding affinity at the 5-HT transporter, VN2222 inhibited 5-HT uptake in vitro both in rat cortical synaptosomes and in mesencephalic cultures and also in vivo when administered locally into the rat ventral hippocampus. After systemic administration, VN2222 exhibited an inverted U-shape effect so the inhibition of [3H]5-HT uptake ex vivo and the increase in 5-HT extracellular levels in microdialysis experiments was observed at low doses of 0.01-0.1 mg/kg whereas higher doses were ineffective. In studies related to 5-HT1A receptor function, 0.01-0.1 microM VN2222 produced a partial inhibition of forskolin-stimulated cAMP formation behaving as a weak agonist of 5-HT1A receptors. In body temperature studies, 5 mg/kg VN2222 produced a mild hypothermic effect in mice, suggesting a weak agonist activity at presynaptic 5-HT1A receptors; much lower doses (0.01-0.5 mg/kg) partially antagonized the hypothermia induced by 8-hydroxy-2-(di-n-propylamino)tetralin (8-OH-DPAT) possibly through 5-HT transporter blockade. In the learned helplessness test in rats, an animal model for antidepressants, 1-5 mg/kg VN2222 reduced significantly the number of escape failures. Consequently, VN2222 is a new compound with a dual effect on the serotonergic system, as 5-HT uptake blocker and 5-HT1A receptor partial agonist, and with a remarkable activity in an animal model of depression with high predictive validity.

8-Hydroxy-2-(di-n-propylamino)tetralin↗
PubMed1979

Holistic versus analytic process models: a reply.

Two classes of stimulus process models are considered in this reply to Dykes and Cooper. It is shown that analytic models which assume that stimuli are initially processed in terms of constituent dimensions do not account for large amounts of published data. It is also shown that the holistic-discriminability model that Dykes and Cooper reject is nonetheless consistent with their results and predicts all of the data for which their analytic model was constructed to account.

Discrimination Learning↗