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PubMed1995

Dissociation between declarative and procedural learning in dementia and depression.

Declarative and procedural learning were assessed in patients with probable Alzheimer's Disease (AD) and major depression, patients with AD and no depression, patients with major depression but no dementia, and a group of age-comparable nondemented and nondepressed normal controls. AD patients showed significant deficits in declarative but not in procedural learning, while depressed nondemented patients showed the opposite pattern (i.e., a significantly worse procedural than declarative learning). Patients with both AD and major depression showed a similar learning pattern to the AD nondepressed group (relatively preserved procedural learning but severe deficits in declarative memory). These findings provide further evidence for the independence between declarative and procedural learning, and demonstrate their different vulnerability in dementia and depressive-like states.

Aged↗
PubMed1997

Supervised Learning Extensions to the CLAM Network.

The contextual layered associative memory (CLAM) has been developed as a self-generating structure which implements a probabilistic encoding scheme. The training algorithms are geared towards the unsupervised generation of a layerable associative mapping ([Thacker and Mayhew, 1989]). We show here that the resulting structure will support layers which can be trained to produce outputs that approximate conditional probabilities of classification. Unsupervised and supervised learning algorithms operate independently permitting the unsupervised representational layer to be developed before supervision is available. The system thus supports learning which is inherently more flexible than conventional node labelling schemes. Copyright 1997 Elsevier Science Ltd. All Rights Reserved.

Journal Article↗
PubMed1997

The prevalence of fragile-X syndrome in an institution for people with learning disability.

The prevalence of Fragile-X syndrome in those with learning disability has been reported. There is little agreement regarding the prevalence rate which varies between 0% and 16%. We report a study investigating the prevalence of Fragile-X syndrome in two institutions for those with learning disability, using DNA testing. We found a rate of 0.7%, which is one of the lowest record rates. We also found that physical signs could be used as a reliable discriminator to determine those likely to have the disorder. We conclude that indiscriminate mass screening of those with learning disability for the Fragile-X syndrome is probably not useful because, in adults, physical signs and a family history of learning disability can predict those likely to have the disorder.

Adult↗
PubMed1993

Synaptic plasticity in the cerebellar cortex and its role in motor learning.

Synaptic plasticity plays a role in the learning capability of brain tissues. Long-term depression (LTD) of parallel fiber synapses in cerebellar Purkinje cells occurs when these synapses are activated in conjunction with climbing fiber synapses. Signal transduction mechanisms underlying LTD have recently been investigated extensively. It has also become apparent that climbing fiber signals encode errors in the motor performance of an animal. It is therefore hypothesized that learning proceeds in cerebellar tissues in such a way that error signals of climbing fibers act to depress by LTD those parallel fiber synapses responsible for the errors. The cerebellum contains a large number of corticonuclear microcomplexes. Each microcomplex is connected to an extracerebellar system and is presumed to endow the system with learning capability. The hypothesis accounts for the adaptation of the vestibuloocular reflex and probably also for other forms of motor and cognitive learning.

Animals↗
PubMed2004

Analysis and design of behavioral experiments to characterize population learning.

In population learning studies, between-subject response differences are an important source of variance that must be characterized to identify accurately the features of the learning process common to the population. Although learning is a dynamic process, current population analyses do not use dynamic estimation methods, do not compute both population and individual learning curves, and use learning criteria that are less than optimal. We develop a state-space random effects (SSRE) model to estimate population and individual learning curves, ideal observer curves, and learning trials, and to make dynamic assessments of learning between two populations and within the same population that avoid multiple hypothesis tests. In an 80-trial study of an NMDA antagonist's effect on the ability of rats to execute a set-shift task, our dynamic assessments of learning demonstrated that both the treatment and control groups learned, yet, by trial 35, the treatment group learning was significantly impaired relative to control. We used our SSRE model in a theoretical study to evaluate the design efficiency of learning experiments in terms of the number of animals per group and number of trials per animal required to characterize learning differences between two populations. Our results demonstrated that a maximum difference in the probability of a correct response between the treatment and control group learning curves of 0.07 (0.20) would require 15 to 20 (5 to 7) animals per group in an 80 (60)-trial experiment. The SSRE model offers a practical approach to dynamic analysis of population learning and a theoretical framework for optimal design of learning experiments.

Algorithms↗
PubMed1993

Behavioral and computational models of spatial attention.

Pigeons pecked for food in a spatially cued choice reaction time (RT) task. A brief (50-ms) white light appeared on a left or right key and probabilistically predicted the location (on either the left or right key) of a subsequent target stimulus. The time between cue and target onset (stimulus onset asynchrony), the base rate of left cues, and the probability that the cue correctly predicted the target (cue validity) were experimentally varied. The mean RT to respond to the target key was faster on correctly cued trials (defining a validity effect), decreased for both valid and invalid trials as stimulus onset asynchrony increased (defining an alerting effect), showed a variety of base-rate effects, and did not depend on cue validity. It is shown with a computational-processing model that dynamic interactions of short-term and associative memory processes are sufficient to produce these attentionlike empirical phenomena.

Animals↗
PubMed2001

Teaching Bayesian reasoning in less than two hours.

The authors present and test a new method of teaching Bayesian reasoning, something about which previous teaching studies reported little success. Based on G. Gigerenzer and U. Hoffrage's (1995) ecological framework, the authors wrote a computerized tutorial program to train people to construct frequency representations (representation training) rather than to insert probabilities into Bayes's rule (rule training). Bayesian computations are simpler to perform with natural frequencies than with probabilities, and there are evolutionary reasons for assuming that cognitive algorithms have been developed to deal with natural frequencies. In 2 studies, the authors compared representation training with rule training; the criteria were an immediate learning effect, transfer to new problems, and long-term temporal stability. Rule training was as good in transfer as representation training, but representation training had a higher immediate learning effect and greater temporal stability.

Algorithms↗
PubMed1992

Effects of L-threo- and erythro-3,4-dihydroxyphenylserine on learning performance and concentrations of brain noradrenaline and its metabolites in rats.

Effects of L-threo and L-erythro-3,4-dihydroxyphenylserine [DOPS, precursor amino acids for noradrenaline (NA)] on the learning performance in a maze paradigm designed to model on the water maze paradigm using a multicomputerized behavioral analysis system were studied. A marked facilitation of learning performance was observed in rats after an intraventricular injection of 5 micrograms L-threo-DOPS (the s-NA precursor), and this effect was inhibited by a simultaneous administration of 1 or 2 micrograms propranolol (a beta-adrenergic antagonist). As concentrations of brain NA, 3-methoxy-4-hydroxyphenylglycol, and normethanephrine were increased by the injection of 5 micrograms L-threo-DOPS, the effect seemed to be derived from activation of beta-adrenoceptors in the CNS by the formed s-NA. On the other hand, an intraventricular injection of 5 micrograms L-erythro-DOPS (the r-NA precursor) attenuated the learning performance, and this effect was probably caused by the formed r-NA from L-erythro-DOPS.

Animals↗
PubMed1996

A generalized hidden Markov model for the recognition of human genes in DNA.

We present a statistical model of genes in DNA. A Generalized Hidden Markov Model (GHMM) provides the framework for describing the grammar of a legal parse of a DNA sequence (Stormo & Haussler 1994). Probabilities are assigned to transitions between states in the GHMM and to the generation of each nucleotide base given a particular state. Machine learning techniques are applied to optimize these probabilities using a standardized training set. Given a new candidate sequence, the best parse is deduced from the model using a dynamic programming algorithm to identify the path through the model with maximum probability. The GHMM is flexible and modular, so new sensors and additional states can be inserted easily. In addition, it provides simple solutions for integrating cardinality constraints, reading frame constraints, "indels", and homology searching. The description and results of an implementation of such a gene-finding model, called Genie, is presented. The exon sensor is a codon frequency model conditioned on windowed nucleotide frequency and the preceding codon. Two neural networks are used, as in (Brunak, Engelbrecht, & Knudsen 1991), for splice site prediction. We show that this simple model performs quite well. For a cross-validated standard test set of 304 genes [ftp:@www-hgc.lbl.gov/pub/genesets] in human DNA, our gene-finding system identified up to 85% of protein-coding bases correctly with a specificity of 80%. 58% of exons were exactly identified with a specificity of 51%. Genie is shown to perform favorably compared with several other gene-finding systems.

Chromosomes, Human↗
PubMed1986

Memory storage and retrieval processes in category learning.

The detailed course of learning is studied for categorization tasks defined by independent or contingent probability distributions over the features of category exemplars. College-age subjects viewed sequences of bar charts that simulated symptom patterns and responded to each chart with a recognition and a categorization judgment. Fuzzy, probabilistically defined categories were learned relatively rapidly when individual features were correlated with category assignment, more slowly when only patterns carried category information. Limits of performance were suboptimal, evidently because of capacity limitations on judgmental processes as well as limitations on memory. Categorization proved systematically related to feature and exemplar probabilities, under different circumstances, and to similarity among exemplars of categories. Unique retrieval cues for exemplar patterns facilitated recognition but entered into categorization only at retention intervals within the range of short-term memory. The findings are interpreted within the framework of a general array model that yields both exemplar-similarity and feature-frequency models as special cases and provides quantitative accounts of the course of learning in each of the categorization tasks studied.

Adult↗
PubMed1995

Is human learning rational?

We can predict and control events in the world via associative learning. Such learning is rational if we come to believe that an associative relationship exists between a pair of events only when it truly does. The statistical metric delta P, the difference between the probability of an outcome event in the presence of the predictor and its probability in the absence of the predictor tells us when and to what extent events are indeed related. Contrary to what is often claimed, humans' associative judgements compare very favourably with the delta P metric, even in situations where multiple predictive cues are in competition for association with the outcome. How do humans achieve this judgmental accuracy? I argue that it is not via the application of an explicit mental version of the delta P rule. Instead, accurate judgements are an emergent property of an associationist learning process of the sort that has become common in adaptive network models of cognition. Such an associationist mechanism is the "means" to a normative or statistical "end".

Association Learning↗
PubMed2003

Genes regulated by learning in the hippocampus.

The enduring changes in long-term memory probably depend on regulation of gene expression in the hippocampus. To seek genes regulated by learning, we used microarray technology to compare hippocampal gene expression in mice undergoing training in the Morris water maze and control mice forced to swim for the same period in the absence of a hidden platform. ANOVA was employed to prioritize genes for further study, and three genes were confirmed by real-time PCR as being regulated during learning. One of the genes was the alpha subunit of the platelet-derived growth factor receptor (Pdgfra); another showed homology to DnaJ and cAMP response element-binding protein 2 (CREB2); and a third was novel. These genes may provide useful insights into the molecular mechanisms of hippocampal learning.

Activating Transcription Factor 4↗
PubMed2007

Adaptive learning and risk taking.

Humans and animals learn from experience by reducing the probability of sampling alternatives with poor past outcomes. Using simulations, J. G. March (1996) illustrated how such adaptive sampling could lead to risk-averse as well as risk-seeking behavior. In this article, the author develops a formal theory of how adaptive sampling influences risk taking. He shows that a risk-neutral decision maker may learn to prefer a sure thing to an uncertain alternative with identical expected value and a symmetric distribution, even if the decision maker follows an optimal policy of learning. If the distribution of the uncertain alternative is negatively skewed, risk-seeking behavior can emerge. Consistent with recent experiments, the model implies that information about foregone payoffs increases risk taking.

Adaptation, Psychological↗
PubMed2006

Physiological properties of zebra finch ventral tegmental area and substantia nigra pars compacta neurons.

The neurotransmitter dopamine plays important roles in motor control, learning, and motivation in mammals and probably other animals as well. The strong dopaminergic projection to striatal regions and more moderate dopaminergic projections to other regions of the telencephalon predominantly arise from midbrain dopaminergic neurons in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA). Homologous dopaminergic cell groups in songbirds project anatomically in a manner that may allow dopamine to influence song learning or song production. The electrophysiological properties of SNc and VTA neurons have not previously been studied in birds. Here we used whole cell recordings in brain slices in combination with tyrosine-hydroxylase immunolabeling as a marker of dopaminergic neurons to determine electrophysiological and pharmacological properties of dopaminergic and nondopaminergic neurons in the zebra finch SNc and VTA. Our results show that zebra finch dopaminergic neurons possess physiological properties very similar to those of mammalian dopaminergic neurons, including broad action potentials, calcium- and apamin-sensitive membrane-potential oscillations underlying pacemaker firing, powerful spike-frequency adaptation, and autoinhibition via D2 dopamine receptors. Moreover, the zebra finch SNc and VTA also contain nondopaminergic neurons with similarities (fast-firing, inhibition by the mu-opioid receptor agonist [d-Ala(2), N-Me-Phe(4), Gly-ol(5)]-enkephalin (DAMGO)) and differences (strong h-current that contributes to spontaneous firing) compared with GABAergic neurons in the mammalian SNc and VTA. Our results provide insight into the intrinsic membrane properties that regulate the activity of dopaminergic neurons in songbirds and add to strong evidence for anatomical, physiological, and functional similarities between the dopaminergic systems of mammals and birds.

Action Potentials↗
PubMedDate not supplied

A preliminary comparison of guided compliance and high-probability instructional sequences as treatment for noncompliance in children with developmental disabilities.

The efficacy of guided compliance and high-probability instructional sequences was compared with two children referred to an outpatient clinic for treatment of noncompliance. Parents were taught to implement the procedures in their homes, and parent-training outcomes for the two interventions were compared in terms of treatment effectiveness, procedural integrity, and parent satisfaction. Levels of compliance were higher under guided compliance than under high-probability instructional sequences. Nevertheless, parents rapidly learned to implement both treatments with a high degree of accuracy and reported equal satisfaction with the procedures.

Adult↗
PubMed1986

Associative induction of posttetanic and long-term potentiation in CA1 neurons of rat hippocampus.

Electrical stimulation of fibers in the stratum radiatum causes an excitatory postsynaptic potential in CA1 neurons of the hippocampus. Other excitatory inputs to or direct depolarization of these CA1 neurons during stimulation of the stratum radiatum caused a subsequent increase in the excitatory postsynaptic potential. This enhancement was characterized as a brief potentiation (2 to 3 minutes, similar to posttetanic potentiation) and a long-term potentiation (presumed to be involved in learning and memory). These potentiations are probably induced by an interaction of the postsynaptic cell or other presynaptic terminals with the test presynaptic terminals.

Action Potentials↗
PubMed1964

ESCAPE FROM SD ASSOCIATED WITH FIXED-RATIO REINFORCEMENT.

Throughout ascending and descending fixed-ratio (FR) sequences, rats were allowed to terminate the FR stimulus control by pressing a time-out (TO) lever. To minimize chance or accidental responses on this second lever, three presses were required to produce the 30-sec S(Delta) period. As FR performance became more "strained," there was an increased predisposition to escape from the time-in stimulus complex. The generality of this finding was extended by obtaining recoverability (independent of the direction of stimulus change) of the FR-TO function in the descending series. Typically, escapes were produced only during the post-reinforcement pause; however, under a mixed FR FR schedule, their occurrence shifted to a point within the inter-reinforcement interval corresponding to the unreinforced completion of the lower ratio component. It appears that the point where the rat can discriminate the size of the ratio requirement will be the place where TOs are imposed. This inference was supported by a substantial increase in TO frequency accompanying a shift from CRF to extinction on the FR lever. Finally, the escape lever was placed on a progressively increasing FR schedule and later extinguished to demonstrate that the TO condition was in fact reinforcing.

Avoidance Learning↗