Nestor A. Schmajuk

Occasion setting : associative learning and cognition in animals

Analogies of Occasion Setting and Pavlovian Conditioning Conditional Learning - an Associative Analysis Mechanisms of Feature-Positive and Feature-Negative Discrimination Learning in an Appetitive Conditioning Paradigm What Can Nontraditional Features Tell Us About Conditioning and Occasion Setting? Pavlovian Feature-Ambiguous Discrimination Perspectives on Modulation - Modulator and Target Focused Views Contextual Control as Occasion Setting Hunger Cues as Modulatory Stimuli The Role of Attention in the Solution of Conditional Discrimination.

Autonomous search by robots and animals: A survey

This paper is a survey of research on autonomous search strategies which originate in engineering and biology. Our motivation is to identify methods of search in an essentially two-dimensional Euclidean space, which can be applied to the area of demining. Such search strategies are based on spatio-temporal distributions. These distributions may be known in advance, because of prior intelligence or through the use of remote sensing, or they may be the result of on-line gathering of information as the search progresses, or of both. We first review the literature on search and coordination which emanates from the field of robotics, we then summarize significant research in the field of animal search, and also discuss relevant results in robotics which are inspired by animal behavior.

Perplexing effects of hippocampal lesions on latent inhibition : A neural network solution

Experimental data indicate that hippocampal lesions might impair, spare, or even facilitate latent inhibition (LI). Furthermore, when LI is impaired by the lesions, it might be reinstated by haloperidol administration. The present article applies a neural network model of classical conditioning (N. A. Schmajuk, Y. W. Lam, & J. A. Gray, 1996) to investigate the possible causes of these puzzling results. According to the model, LI is manifested because preexposure of the conditioned stimulus (CS) reduces Novelty, defined as proportional to the sum of the mismatches between predicted and observed events, thereby reducing attention to the CS and retarding conditioning. It is assumed that hippocampal lesions affect the prediction of events. Computer simulations reveal that, depending on the behavioral protocol (i.e., procedure and total time of CS preexposure), Novelty in hippocampal lesioned animals might be larger, equal, or smaller (corresponding to smaller, equal, or larger LI) than in normal controls. Reinstatement of LI by haloperidol administration is explained by assuming that dopaminergic antagonists decrease the value of Novelty, when Novelty increases following hippocampal lesions.

Latent inhibition of the rat eyeblink response: Effect of hippocampal aspiration lesions

The effect of hippocampal aspiration lesions on latent inhibition of eyeblink conditioning in the restrained rat preparation was examined. Rats received either sham, cortical control, or hippocampal aspiration lesions. Control animals, but not animals with hippocampal lesions, showed slower conditioning after being preexposed to the conditioned stimulus (latent inhibition). Together with previous results regarding the effect of hippocampal lesions in acquisition and extinction of delay conditioning, the present study suggests that the restrained rat preparation may serve as a reliable way of investigating hippocampal participation in different classical conditioning paradigms.

Timing in simple conditioning and occasion setting: a neural network approach

We present a neural network model of Pavlovian conditioning in which a timing mechanism, by which a CS can predict when the US is presented, activates an architecture in which a stimulus acts as a simple CS and/or as an occasion setter. In the model, stimuli evoke multiple traces of different duration and amplitude, peaking at different times after CS presentation [Grossberg and Schmajuk, 1989. Neural Netw. 2, 79-102]. These traces compete to become associated directly and indirectly (through hidden units) with the US [Schmajuk and DiCarlo, 1992. Psychol. Rev. 99, 268-305]. The output of the system predicts the value, moment, and duration of presentation of reinforcement. Importantly, in contrast to the model by Schmajuk and DiCarlo [Schmajuk and DiCarlo, 1992. Psychol. Rev. 99, 268-305], in the present model a stimulus may assume different roles (simple CS, occasion setter, or both) at different time moments. Moreover, while in the Schmajuk and DiCarlo model [Schmajuk and DiCarlo, 1992. Psychol. Rev. 99, 268-305], competition between CSs is purely associative, in the present model competition between CSs is both associative and temporal. CSs compete to predict not only the presence and the intensity of the US, but also its temporal characteristics: time of presentation and duration. The model is able to address both the temporal and associative properties of simple conditioning, compound conditioning, and occasion setting.

Attentional, associative, and configural mechanisms in extinction.

The participation of attentional and associative mechanisms in extinction, spontaneous recovery, external disinhibition, renewal, reinstatement, and reacquisition was evaluated through computer simulations with an extant computational model of classical conditioning (N. A. Schmajuk, Y. Lam, & J. A. Gray, 1996; N. A. Schmajuk & J. A. Larrauri, 2006). The model assumes that attention to stimuli (controlled by environmental novelty) and associations between stimuli interact during memory storage (learning) and retrieval (performance). Computer simulations indicated that a combination of attentional and associative mechanisms might be sufficient to describe most of the properties of extinction. However, configural mechanisms seem necessary to describe the properties of cues that precede the target stimulus during extinction (extinction cues) and might improve the description of some experimental results regarding the associative properties of the extinction context. These configural mechanisms can be easily integrated into the present version of the model.

Attention, configuration, and hippocampal function.

We present a neural network that characterizes a remarkably large number of classical conditioning paradigms and describes the effects of many neurophysiological manipulations. First, the network 1) describes behavior in real time 2) comprises simple and configural stimulus representations, and 3) includes attentional control of storage and retrieval. Second, mapping of the network onto the brain can be summarized by several information processing loops: 1) a hippocampal‐cortical configural loop, 2) a hippocampal‐cerebellar conditioned‐response loop, 3) a hippocampal‐accumbens‐thalamic attentional loop, and 4) a hippocampal‐medial raphe‐medial septum error loop. Third, within this global view of brain function, it is assumed that the hippocampal formation computes 1) the aggregate prediction of environmental events and 2) the error signals for cortical learning. These assumptions are supported by rigorous computer simulations consistent with a large body of data on hippocampal and septal neural activity, induction and blockade of hippocampal long‐term potentiation, administration of cholinergic agonists and antagonists, administration of haloperidol, and selective and nonselective hippocampal and cortical lesions.

Stimulus configuration, occasion setting, and the hippocampus

N. A. Schmajuk, J. Lamoureux, and P. C. Holland (in press) showed that an extension of a neural network model introduced by N. A. Schmajuk and J. J. DiCarlo (1992) characterizes many of the differences between simple conditioning and occasion setting. In the framework of this model, it is proposed that the hippocampus modulates (a) the competition among simple and complex stimuli to establish associations with the unconditioned stimulus, and (b) the configuration of simple stimuli into complex stimuli. Under the assumptions that (a) nonselective lesions of the hippocampal formation impair both configuration and competition, and (b) selective lesions of the hippocampus proper impair only stimulus configuration, the model correctly describes the effects of these lesions on paradigms in which stimuli act as occasion setters.

Nucleus accumbens, entorhinal cortex and latent inhibition : A neural network model

A neural network model of classical conditioning (Schmajuk, Lam, and Gray, J. Exp. Psychol.: Anim. Behav. Process, 22, 1996, 321-349) is applied to the description of the neural substrates of latent inhibition. Experimental data suggest that latent inhibition might be controlled by a circuit that involves the hippocampus, the entorhinal cortex, the nucleus accumbens, and the mesolimbic dopaminergic projection from the ventral tegmental area to the accumbens. By mapping different nodes and connections in the model onto this brain circuit, computer simulations demonstrate that, in most cases, the model provides a good quantitative description of: (1) the impairment of latent inhibition by lesions of the shell of the nucleus accumbens; (2) the restoration of latent inhibition by haloperidol following lesions of the shell; (3) the preservation of latent inhibition by lesions of the core of the nucleus accumbens; (4) the facilitation of latent inhibition by combined shell core lesions and by core lesions with extended conditioning; (5) the impairment of latent inhibition following lesions of the entorhinal cortex or the hippocampus; and (6) the restoration of latent inhibition by haloperidol following lesions of the entorhinal cortex and ventral subiculum. In addition, the model is able to describe neural activity in the nucleus accumbens.

Experimental challenges to theories of classical conditioning: Application of an attentional model of storage and retrieval.

Several studies have recently challenged the accuracy of traditional models of classical conditioning that account for some experimental data in terms of a storage deficit. Among other results, it has been reported that extinction of the blocking or overshadowing stimulus results in the recovery of the response to the blocked or overshadowed stimulus, backward blocking shows spontaneous recovery, extinction of the training context results in the recovery from latent inhibition, interposing a delay between conditioning and testing in latent inhibition increases latent inhibition, and latent inhibition antagonizes overshadowing. An existing neural network model of classical conditioning (N. A. Schmajuk, Y. Lam, & J. A. Gray, 1996), which includes an attentional mechanism controlling both storage and retrieval of associations, is able to quantitatively describe these results.