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Results for “Predictive Learning Models”

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At least 973 records · Page 54Linked to original sources

PubMed1986

Eye-hand-coordination: a model for computing reaction times in a visually guided reach task.

A model is described which provides a simple algorithm to compute the reaction times of saccadic eye movements and reach movements aimed at a single visual target. It is assumed, that the two movements are prepared in parallel and initiated independently unless the preparation of the saccade for some reason takes longer than the preparation of the reach movement. In the latter case the final command to execute the reach movement is synchronized with that to execute the eye movement and therefore the corresponding reaction times are highly correlated in a one-to-one relationship. Random variables are used to predict sets of data that are directly comparable with the experimental results. The algorithm includes the effects of daily practice (learning). The structure of the model and its computational results will be compared with the physiological data from monkey and man.

Algorithms↗

PubMed1996

The expectancy bias model of selective associations: the relationship of judgements of CS dangerousness, CS-UCS similarity and prior fear to a priori and a posteriori covariation assessments.

This paper describes three experiments examining predictions from the expectancy bias model of selective associations (Davey, 1995). In a simulated 'threat' conditioning procedure, Experiment 1 showed that UCS expectancy following both ontogenetic and phylogenetic CSs was significantly predicted by: (1) ratings of the dangerousness of the CS, perceptions of CS-UCS similarity, and level of prior fear to the CS; and (2) ratings of CS-UCS similarity on the dimensions of valence, arousal and anxiety. Experiment 2 used a covariation assessment procedure which confirmed the findings of Experiment 1, and also showed that both phylogenetic and ontogenetic fear-relevant CSs exhibited both a priori and a posteriori covariation biases. Experiment 3 found that Ss high and low in fear to a fear-relevant CS exhibited a significant a priori UCS expectancy bias, but this bias was significantly larger in high fear Ss. Only high fear Ss exhibited an a posteriori covariation bias. These results are consistent with predictions from the expectancy bias model.

Adolescent↗

PubMedDate not supplied

A consultation system for insulin therapy.

This paper describes a computer system to advice on insulin therapy for diabetic in-patients. A mathematical model was developed to describe the effect of insulin on blood glucose (BG) level. The system uses an adaptive approach to analyse the response to an applied insulin dosage. It learns the patient's individual parameters. All conventional injection and insulin pump regimens are supported. The individualised model is used to predict BG level of the proposed insulin dosage. The system uses a generate-reject strategy to output optimum insulin therapy in terms of optimum BG. The predictive capability of the system was tested and it is able to predict BG with a precision of 2.5 mmol/l after 3 days and 6 days of insulin pump treatment and conventional injection therapy, respectively.

Blood Glucose Self-Monitoring↗

PubMed2003

Effects of stimulus frequency and age on bidirectional synaptic plasticity in the dentate gyrus of freely moving rats.

We investigated the frequency-dependent transition from homosynaptic long-term depression (LTD) to long-term potentiation (LTP) at the lateral perforant pathway/dentate gyrus synapse in adult (90 days of age) and immature (15 days of age) awake, freely moving rats. Dentate-evoked field potentials were recorded and analyzed using the population spike amplitude and the field EPSP slope measures following sustained stimulation (900 pulses) of the lateral perforant pathway at various frequencies (1, 3, 7, 30, 50, or 200 Hz). Our results indicate that both the strength and the direction (LTP or LTD) of synaptic plasticity vary as a function of activation frequency: sustained low-frequency stimulation ranging from 1 to 7 Hz results in depression of activated synapses, whereas high-frequency stimulation (30-200 Hz) produces potentiation. In addition, a significant (P < 0.01) ontogenetic shift in the frequency of transition from LTD to LTP was observed; the transition frequency in immature animals was significantly lower than that obtained in adult animals. These observations agree strongly with the prediction of the Bienenstock-Cooper-Munro theory of synapse modification, indicating perhaps a neurophysiological basis for this theoretical model of learning in the dentate gyrus of awake behaving rats.

Action Potentials↗

PubMed1999

Middle ear effusion: rate and risk factors in Australian children attending day care.

There have been no previous longitudinal studies of otitis media conducted in non-Aboriginal Australian children. This paper describes the rate and risk factors for middle ear effusion (MEE) in children attending day care in Darwin, Australia. A prospective cohort study of 252 children under 4 years was conducted in 9 day care centres over 12 fortnights between 24 March and 15 September 1997. Tympanometry was conducted fortnightly and multivariate analysis used to determine risk factors predicting MEE. The outcome of interest was the rate of type B tympanograms per child detected in either ear at fortnightly examinations. After adjusting for clustering by child, MEE was detected on average 4.4 times in 12 fortnights (37% of all examinations conducted). Risk factors associated with presence of effusion were younger age, a family history of ear infection, previous grommets (tympanostomy tubes), ethnicity and the day care centre attended. A history of wheeze appeared protective. These effects were modest (RR 0.57-1.70). Middle ear effusion is very common in children attending day care in Darwin. This has clinical importance, since MEE during early childhood may affect optimal hearing, learning and speech development. There is little scope for modification for many of the risk factors for MEE predicted by this model. Further study of the day care environment is warranted.

Child Day Care Centers↗

PubMed2004

Addiction motivation reformulated: an affective processing model of negative reinforcement.

This article offers a reformulation of the negative reinforcement model of drug addiction and proposes that the escape and avoidance of negative affect is the prepotent motive for addictive drug use. The authors posit that negative affect is the motivational core of the withdrawal syndrome and argue that, through repeated cycles of drug use and withdrawal, addicted organisms learn to detect interoceptive cues of negative affect preconsciously. Thus, the motivational basis of much drug use is opaque and tends not to reflect cognitive control. When either stressors or abstinence causes negative affect to grow and enter consciousness, increasing negative affect biases information processing in ways that promote renewed drug administration. After explicating their model, the authors address previous critiques of negative reinforcement models in light of their reformulation and review predictions generated by their model.

Affect↗

PubMed2006

Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal.

The authors explore the division of labor between the basal ganglia-dopamine (BG-DA) system and the orbitofrontal cortex (OFC) in decision making. They show that a primitive neural network model of the BG-DA system slowly learns to make decisions on the basis of the relative probability of rewards but is not as sensitive to (a) recency or (b) the value of specific rewards. An augmented model that explores BG-OFC interactions is more successful at estimating the true expected value of decisions and is faster at switching behavior when reinforcement contingencies change. In the augmented model, OFC areas exert top-down control on the BG and premotor areas by representing reinforcement magnitudes in working memory. The model successfully captures patterns of behavior resulting from OFC damage in decision making, reversal learning, and devaluation paradigms and makes additional predictions for the underlying source of these deficits.

Animals↗

PubMed2004

A revised methodology for research on metamemory: Pre-judgment Recall and Monitoring (PRAM).

A revised methodology is described for research on metacognitive monitoring, especially judgments of learning (JOLs), to investigate psychological processing that previously has been only hypothetical and unobservable. During data collection a new stage of recall occurs just prior to the JOL, so that during data analysis the items can be partitioned into subcategories to measure the degree of JOL accuracy in ways that are more analytic than was previously possible. A weighted-average combinatorial rule allows the component measures of JOL accuracy to be combined into the usual overall measure of metacognitive accuracy. An example using the revised methodology offers a new explanation for the delayed-JOL effect, in which delayed JOLs are more accurate than immediate JOLs for predicting recall.

Humans↗

PubMed2004

Why neural networks should not be used for HIV-1 protease cleavage site prediction.

UNLABELLED: Several papers have been published where nonlinear machine learning algorithms, e.g. artificial neural networks, support vector machines and decision trees, have been used to model the specificity of the HIV-1 protease and extract specificity rules. We show that the dataset used in these studies is linearly separable and that it is a misuse of nonlinear classifiers to apply them to this problem. The best solution on this dataset is achieved using a linear classifier like the simple perceptron or the linear support vector machine, and it is straightforward to extract rules from these linear models. We identify key residues in peptides that are efficiently cleaved by the HIV-1 protease and list the most prominent rules, relating them to experimental results for the HIV-1 protease. MOTIVATION: Understanding HIV-1 protease specificity is important when designing HIV inhibitors and several different machine learning algorithms have been applied to the problem. However, little progress has been made in understanding the specificity because nonlinear and overly complex models have been used. RESULTS: We show that the problem is much easier than what has previously been reported and that linear classifiers like the simple perceptron or linear support vector machines are at least as good predictors as nonlinear algorithms. We also show how sets of specificity rules can be generated from the resulting linear classifiers. AVAILABILITY: The datasets used are available at http://www.hh.se/staff/bioinf/

Algorithms↗

PubMed2005

KinasePhos: a web tool for identifying protein kinase-specific phosphorylation sites.

KinasePhos is a novel web server for computationally identifying catalytic kinase-specific phosphorylation sites. The known phosphorylation sites from public domain data sources are categorized by their annotated protein kinases. Based on the profile hidden Markov model, computational models are learned from the kinase-specific groups of the phosphorylation sites. After evaluating the learned models, the model with highest accuracy was selected from each kinase-specific group, for use in a web-based prediction tool for identifying protein phosphorylation sites. Therefore, this work developed a kinase-specific phosphorylation site prediction tool with both high sensitivity and specificity. The prediction tool is freely available at http://KinasePhos.mbc.nctu.edu.tw/.

Computational Biology↗

PubMed2003

Cranial epigastric perforator flap: a rat model of a true perforator flap.

The major advantage of a true perforator flap is the ability to capture the skin portion of what previously was a musculocutaneous flap, while totally excluding the muscle for function preservation. To understand better the physiology and dynamics of this flap subtype, a comparable and reliable animal model is essential. This has now been accomplished in the Sprague-Dawley rat using the same abdominal skin territory of the standard rat transverse rectus abdominis musculocutaneous flap, but differing in that all rectus abdominis fascial perforators are isolated via an intramuscular dissection back to the cranial epigastric artery source vessel. Hence, this has appropriately been termed the cranial epigastric perforator flap. From a series of eight rats to date, consistent survival of this flap was as predicted. The dissection itself can be somewhat tedious, but it became easier with experience, making this an excellent training model for learning proper technique in the elevation of any true perforator flap.

Animals↗

PubMed2001

Cavity approach to noisy learning in nonlinear perceptrons.

We analyze the learning of noisy teacher-generated examples by nonlinear and differentiable student perceptrons using the cavity method. The generic activation of an example is a function of the cavity activation of the example, which is its activation in the perceptron that learns without the example. Mean-field equations for the macroscopic parameters and the stability condition yield results consistent with the replica method. When a single value of the cavity activation maps to multiple values of the generic activation, there is a competition in learning strategy between preferentially learning an example and sacrificing it in favor of the background adjustment. We find parameter regimes in which examples are learned preferentially or sacrificially, leading to a gap in the activation distribution. Full phase diagrams of this complex system are presented, and the theory predicts the existence of a phase transition from poor to good generalization states in the system. Simulation results confirm the theoretical predictions.

Biophysical Phenomena↗

PubMed1995

Reflection and critical incident analysis: ethical and moral implications of their use within nursing and midwifery education.

Despite the dearth of rigorous empirical investigation, reflection and reflective practice have become buzz words in nursing and midwifery education. Reflection and critical incident analysis may be tools which can facilitate the integration of theory and practice. It is proposed that in the absence of explicit and thorough preparation of lecturers and students, together with very careful curriculum planning, these activities may be counter-productive or even harmful. In the absence of structure, reflection and associated critical incident analysis may lead to student disaffection or, worse, the potential for actual psychological disturbance. Empirical studies on the use of identified models of reflection and critical incident analysis are urgently needed to assist nursing and midwifery lecturers and students to achieve predictable learning outcomes for this potentially valuable activity.

Attitude of Health Personnel↗

PubMed2006

The forecast of the postoperative survival time of patients suffered from non-small cell lung cancer based on PCA and extreme learning machine.

In this paper, a new effective model is proposed to forecast how long the postoperative patients suffered from non-small cell lung cancer will survive. The new effective model which is based on the extreme learning machine (ELM) and principal component analysis (PCA) can forecast successfully the postoperative patients' survival time. The new model obtains better prediction accuracy and faster convergence rate which the model using backpropagation (BP) algorithm and the Levenberg-Marquardt (LM) algorithm to forecast the postoperative patients' survival time can not achieve. Finally, simulation results are given to verify the efficiency and effectiveness of our proposed new model.

Algorithms↗

PubMed2004

Functional magnetic resonance imaging examination of two modular architectures for switching multiple internal models.

An internal model is a neural mechanism that can mimic the input-output properties of a controlled object such as a tool. Recent research interests have moved on to how multiple internal models are learned and switched under a given context of behavior. Two representative computational models for task switching propose distinct neural mechanisms, thus predicting different brain activity patterns in the switching of internal models. In one model, called the mixture-of-experts architecture, switching is commanded by a single executive called a "gating network," which is different from the internal models. In the other model, called the MOSAIC (MOdular Selection And Identification for Control), the internal models themselves play crucial roles in switching. Consequently, the mixture-of-experts model predicts that neural activities related to switching and internal models can be temporally and spatially segregated, whereas the MOSAIC model predicts that they are closely intermingled. Here, we directly examined the two predictions by analyzing functional magnetic resonance imaging activities during the switching of one common tool (an ordinary computer mouse) and two novel tools: a rotated mouse, the cursor of which appears in a rotated position, and a velocity mouse, the cursor velocity of which is proportional to the mouse position. The switching and internal model activities temporally and spatially overlapped each other in the cerebellum and in the parietal cortex, whereas the overlap was very small in the frontal cortex. These results suggest that switching mechanisms in the frontal cortex can be explained by the mixture-of-experts architecture, whereas those in the cerebellum and the parietal cortex are explained by the MOSAIC model.

Adult↗

PubMed2004

Climbing neuronal activity as an event-based cortical representation of time.

The brain has the ability to represent the passage of time between two behaviorally relevant events. Recordings from different areas in the cortex of monkeys suggest the existence of neurons representing time by increasing (climbing) activity, which is triggered by a first event and peaks at the expected time of a second event, e.g., a visual stimulus or a reward. When the typical interval between the two events is changed, the slope of the climbing activity adapts to the new timing. We present a model in which the climbing activity results from slow firing rate adaptation in inhibitory neurons. Hebbian synaptic modifications allow for learning the new time interval by changing the degree of firing rate adaptation. This event-based representation of time is consistent with Weber's law in interval timing, according to which the error in estimating a time interval is proportional to the interval length.

Action Potentials↗

PubMed2003

Motor adaptation to different dynamic environments is facilitated by indicative context stimuli.

When humans are exposed to external forces while performing arm movements, they adapt by compensating for these novel forces. The basis of this learning process is thought to be a neural representation that models the relation between all forces acting upon the system and the kinematic effects they produce, called inverse dynamic model (IDM). The present study investigated whether and how the predictability of a given external force affects the selection of an appropriate motor response to compensate for such force. Adult human subjects ( N=32) held a handle that could rotate around the elbow joint and learned to perform goal-directed forearm flexion movements, while an external velocity-dependent negative damping force was applied that assisted forearm movement. Subjects were randomly assigned to two groups. In the associative group, the applied damping force was always associated with a specific initial position. Thus, after initial learning, the force application became predictable. In the non-associative group, where the same movements were performed, the applied force was independent of the initial position, so that no association between force and location could be formed. We found that only the associative group significantly reduced target error when damping was present. That is, the location cue aided these subjects in generating dynamic responses in the appropriate limb. Our results indicate that motor adaptation to different dynamic environments can be facilitated by indicative stimuli.

Adult↗

PubMedDate not supplied

Opponent interactions between serotonin and dopamine.

Anatomical and pharmacological evidence suggests that the dorsal raphe serotonin system and the ventral tegmental and substantia nigra dopamine system may act as mutual opponents. In the light of the temporal difference model of the involvement of the dopamine system in reward learning, we consider three aspects of motivational opponency involving dopamine and serotonin. We suggest that a tonic serotonergic signal reports the long-run average reward rate as part of an average-case reinforcement learning model; that a tonic dopaminergic signal reports the long-run average punishment rate in a similar context; and finally speculate that a phasic serotonin signal might report an ongoing prediction error for future punishment.

Animals↗