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PubMed2005

A neural network model of foraging decisions made under predation risk.

This article develops the cognitive-emotional forager (CEF) model, a novel application of a neural network to dynamical processes in foraging behavior. The CEF is based on a neural network known as the gated dipole, introduced by Grossberg, which is capable of representing short-term affective reactions in a manner similar to Solomon and Corbit's (1974) opponent process theory. The model incorporates a trade-off between approach toward food and avoidance of predation under varying levels of motivation induced by hunger. The results of simulations in a simple patch selection paradigm, using a lifetime fitness criterion for comparison, indicate that the CEF model is capable of nearly optimal foraging and outperforms a run-of-luck rule-of-thumb model. Models such as the one presented here can illuminate the underlying cognitive and motivational components of animal decision making.

Animals↗
PubMed1992

Optimizing the use of information: strategic control of activation of responses.

Recent studies indicate that subjects may respond to visual information during either an early parallel phase or a later focused phase and that the selection of the relevant phase is data driven. Using the noise-compatibility paradigm, we tested the hypothesis that this selection may also be strategic and context driven. At least part of the interference effect observed in this paradigm is due to response activation during the parallel-processing phase. We manipulated subjects' expectancies for compatible and incompatible noise in 4 experiments and effectively modulated the interference effect. The results suggest that expectancies about the relative utility of the information extracted during the parallel and focused phases determine which phase is used to activate responses.

Adult↗
PubMed2004

A theory of causal learning in children: causal maps and Bayes nets.

The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.

Adult↗
PubMed2007

The role of similarity in human associative learning.

In 2 experiments, humans received sequences of patterns that were similar (AX-->BX, AY-->BY, AZ-->BZ) or dissimilar (CX-->DY, CY-->DZ, CZ-->DX). The patterns were portrayed as bugs that could be eliminated with 2 insecticide sprays (red or blue). Either spray eliminated bugs with Features A and C, and participants learned by trial and error to use one spray (e.g., red) to eliminate bugs with Feature B and the other spray (e.g., blue) to eliminate those with Feature D. In Experiment 1, participants' spray choice for bugs with Feature A came to match that used to eliminate bugs with Feature B, but there was no such associative transfer between Features C and D. That is, similarity promoted associative transfer of responding between paired patterns when the features used to manipulate similarity (i.e., X, Y, and Z) were irrelevant. In Experiment 2, in which X, Y, and Z were relevant to the solution of configural discrimination, similarity hindered such associative transfer. These results complement those found in pigeons (R. A. Rescorla & D. J. Gillan, 1980) and indicate that similarity should not be accorded independent status as a principle of associative learning.

Association Learning↗
PubMed2003

Linear transformations of the payoff matrix and decision criterion learning in perceptual categorization.

The effects of payoff-matrix multiplication, payoff-matrix addition, the presence of long-run gains versus long-run losses, category discriminability, and base rate on decision criterion learning were examined in 2 perceptual categorization experiments. Observers were found to be sensitive to the effects of payoff-matrix multiplication (and category discriminability) on the steepness of the objective reward function in line with predictions from the flat-maxima hypothesis and contrary to the predictions from the payoff-variance hypothesis. Decision criterion learning was best in base-rate conditions, was worst when losses were associated with incorrect responding, and was intermediate when no losses were associated with incorrect responding. This performance profile was well captured by the competition between reward and accuracy (COBRA) hypothesis. A hybrid model framework that instantiates both the flat-maxima and COBRA hypotheses was necessary to account for the data from both experiments.

Attention↗
PubMed2006

The influence of prior choices on current choice.

Three pigeons chose between random-interval (RI) and tandem, continuous-reinforcement, fixed-interval (crf-FI) reinforcement schedules by pecking either of two keys. As long as a pigeon pecked on the RI key, both keys remained available. If a pigeon pecked on the crf-FI key, then the RI key became unavailable and the crf-FI timer began to time out. With this procedure, once the RI key was initially pecked, the prospective value of both alternatives remained constant regardless of time spent pecking on the RI key without reinforcement (RI waiting time). Despite this constancy, the rate at which pigeons switched from the RI to the crf-FI decreased sharply as RI waiting time increased. That is, prior choices influenced current choice-an exercise effect. It is argued that such influence (independent of reinforcement contingencies) may serve as a sunk-cost commitment device in self-control situations. In a second experiment, extinction was programmed if RI waiting time exceeded a certain value. Rate of switching to the crf-FI first decreased and then increased as the extinction point approached, showing sensitivity to both prior choices and reinforcement contingencies. In a third experiment, crf-FI availability was limited to a brief window during the RI waiting time. When constrained in this way, switching occurred at a high rate regardless of when, during the RI waiting time, the crf-FI became available.

Animals↗
PubMed2003

Procedural learning in perceptual categorization.

In two experiments, observers learned two types of category structures: those in which perfect accuracy could be achieved via some explicit rule-based strategy and those in which perfect accuracy required integrating information from separate perceptual dimensions at some predecisional stage. At the end of training, some observers were required to switch their hands on the response keys, whereas the assignment of categories to response keys was switched for other observers. With the rule-based category structures, neither change in response instructions interfered with categorization accuracy. However, with the information-integration structures, switching response key assignments interfered with categorization performance, but switching hands did not. These results are consistent with the hypothesis that abstract category labels are learned in rule-based categorization, whereas response positions are learned in information-integration categorization. The association to response positions also supports the hypothesis of a procedural-learning-based component to information integration categorization.

Association Learning↗
PubMed2005

Sequential task predictability in task switching.

Many studies of task switching have found that a prolonged preparation time reduces switch costs. An alternative manipulation of task preparation is based on sequential task predictability, rather than preparation time. In Experiments 1 and 2 of the present study, participants performed explicitly instructed task sequences (i.e., AABB) and were then transferred to a random sequence. The observed benefit of predictability-based task preparation was not switch specific. In Experiment 3, the participants changed from random to predictable tasks. The observed predictability benefit again was not switch specific. The data thus suggest that task switching does not necessarily require a switch-specific reconfiguration process. Rather, task-specific control processes may be needed in both task switches and repetitions.

Association Learning↗
PubMed2000

A comparison of two response time models applied to perceptual matching.

Two models, a Poisson race model and a diffusion model, are fit to data from a perceptual matching task. In each model, information about the similarity or the difference between two stimuli accumulates toward thresholds for either response. Stimulus variables are assumed to influence the rate at which information accumulates, and response variables are assumed to influence the level of the response thresholds. Three experiments were conducted to assess the performance of each model. In Experiment 1, observers performed under different response deadlines; in Experiment 2, response bias was manipulated by changing the relative frequency of same and different stimuli. In Experiment 3, stimulus pairs were presented at three eccentricities: foveal, parafoveal, and peripheral. We examined whether the race and diffusion models could fit the response time and accuracy data through changes only in response parameters (for Experiments 1 and 2) or stimulus parameters (for Experiment 3). Comparisons between the two models suggest that the race model, which has not been studied extensively, can account for perceptual matching data at least as well as the diffusion model. Furthermore, without the constraints on the parameters provided by the experimental conditions, the diffusion and the race models are indistinguishable. This finding emphasizes the importance of fitting models across several conditions and imposing logical psychological constraints on the parameters of models.

Adult↗
PubMed2002

Memory seeding: representations underlying quantitative estimations.

N. R. Brown and R. S. Siegler (1996) found that training participants on a subset of country populations improved estimations for novel transfer country populations, an effect called seeding that remained intact over time. They attributed this effect to the abstraction by participants of a general metric framework for estimating populations not dependent on specific country anchors. In a series of 3 follow-up experiments, the authors found that training on seed populations produces both general metric information and durable specific country information. Moreover, minimal amounts of general (mean or range of populations) or specific (1 or 3 countries) information made available for inspection while estimating produced a significant seeding effect. Retention over long intervals was facilitated by both presenting 3 seed countries as opposed to 1 and providing names for the seed countries.

Adult↗
PubMed1999

A long-term stress exposure impairs maze learning performance in rats.

To elucidate hippocampal dysfunctions following chronic stress exposure, we evaluated the effect of chronic stress on maze learning performance, as assessed by a radial eight-arm maze task. In the 12-week stress sessions, male rats in the stress group were exposed to the stress of a 15-min immersion in cold water once a day and, rats in the control group were slightly handled. Rats in the stress group performed significantly poorly during the acquisition period (P < 0.01) and required more trials to attain at least seven correct choices in the first eight choices for five consecutive trials (P < 0.05). Together with our previous findings that chronic stress exposure damages the hippocampus histologically, we concluded that chronic stress exposure resulted in an impairment of maze learning performance, probably due to hippocampal damages.

Animals↗
PubMed2006

Perspectives of probabilistic inferences: Reinforcement learning and an adaptive network compared.

The assumption that people possess a strategy repertoire for inferences has been raised repeatedly. The strategy selection learning theory specifies how people select strategies from this repertoire. The theory assumes that individuals select strategies proportional to their subjective expectations of how well the strategies solve particular problems; such expectations are assumed to be updated by reinforcement learning. The theory is compared with an adaptive network model that assumes people make inferences by integrating information according to a connectionist network. The network's weights are modified by error correction learning. The theories were tested against each other in 2 experimental studies. Study 1 showed that people substantially improved their inferences through feedback, which was appropriately predicted by the strategy selection learning theory. Study 2 examined a dynamic environment in which the strategies' performances changed. In this situation a quick adaptation to the new situation was not observed; rather, individuals got stuck on the strategy they had successfully applied previously. This "inertia effect" was most strongly predicted by the strategy selection learning theory.

Adult↗
PubMedDate not supplied

Vector representation of associative learning.

I. P. Pavlov [12] has shown that conditioned reflexes are selective both with respect to conditioned stimuli and to conditioned reflexes elicited by those conditioned stimuli. At the neuronal level selective aspects of conditioned stimuli are based on detectors selectively tuned to respective stimuli. The selective aspects of conditioned reflexes are due to command neurons representing specific unconditioned reflexes. It can be assumed that conditioned reflexes result from association between selective detectors and specific command neurons. The detectors activated by a conditioned stimulus constitute a combination of excitations--a detector excitation vector. The detector excitation vector acts on a command neuron via a set of plastic synapses--a synaptic weight vector. Plastic synapses are modified in the process of learning making command neuron selectively tuned to a specific conditioned stimulus. The selective tuning of a particular command neuron to a specific excitation vector referred to a conditioned stimulus is a basis of associative learning. The probabilities of conditioned reflexes elicited by conditioned and differential stimuli implicitly contain information concerning excitation vectors that encode respective stimuli. Contribution of the vector code to associative learning was explored combining differential color conditioning with intracellular recording from color-coding neurons. It was shown that colors in carps and monkeys are represented on a hypersphere in the four-dimensional space similar to human color space. The basis of the color space is constituted by red-green, blue-yellow, brightness and darkness neurons.

Animals↗
PubMed2002

Probabilistic classification learning in Tourette syndrome.

Tourette syndrome (TS) is characterised by stereotyped involuntary movements, called tics. Some evidence suggests that structural and functional abnormalities of the basal ganglia may explain these motor symptoms. In this study, the probabilistic classification learning (PCL) test was used to evaluate basal ganglia functions in 10 children with less severe tics (Yale Global Tic Severity Scale (YGTSS) scores<30) and in 10 children with more severe symptoms (YGTSS score>30). In the PCL task, participants are asked to decide whether different combinations of four geometric forms (cues) predict rainy or sunny weather. Each cue is probabilistically related to a weather outcome, and feedback is provided after each decision. After completion of the probabilistic stimulus-response learning procedure, subjects received a transfer test to assess explicit knowledge about the cues. The children with TS exhibited impaired learning in the PCL task in comparison with the 20 healthy control subjects. This impairment was more pronounced in the TS patients with severe symptoms, and there was a significant negative relationship between the final classification performance and the YGTSS scores. The patients showed normal learning in the transfer test. These results suggest that the neostriatal habit learning system, which may play a central role in the acquisition of probabilistic associations, is dysfunctional in TS, especially in the case of more severe motor symptoms. The classification performance and the severity of tics were independent of the explicit knowledge obtained during the test.

Adolescent↗
PubMed2003

Effect of nitric oxide synthase inhibition on the manipulative behaviour of Sepia officinalis.

Nitric oxide (NO), produced by nitric oxide synthase (NOS) in brain tissue, is essential for a variety of kinds of learning in vertebrates. In invertebrates, there are clear examples of an association between NO signalling and olfaction, feeding behaviour and learning. The role of NO as a neurotransmitter in the manipulative behaviour of Sepia officinalis was tested. Manipulative behaviour requires extensive chemotactile sensory processing, fine motor control and probably motor learning processes. NADPH-diaphorase activity (a reliable histochemical marker for nitric oxide synthase) was found in sensory epithelia and in the axial nerve cord of the arms. NOS inhibitor injections (L-NAME) produced an increase in the latency of prey paralysis. By placing mechanical constraints on the base of the fifth periopods of the crab, we prevented the cuttlefish from injecting cephalotoxin and, thus, forced it to change injection sites. We showed that L-NAME pretreatment did not affect the flexibility of the manipulative behaviour. The implications of the involvement of NO in the acquisition of chemo-tactile information and in the programming of the motor skills of the manipulative behaviour is discussed.

Animals↗