Timing for the absence of a stimulus: the gap paradigm reversed.

Contrary to data showing sensitivity to nontemporal properties of timed signals, current theories of interval timing assume that animals can use the presence or absence of a signal as equally valid cues as long as duration is the most predictive feature. Consequently, the authors examined rats' behavior when timing the absence of a visual or auditory stimulus in trace conditioning and in a "reversed" gap procedure. Memory for timing was tested by presenting the stimulus as a reversed gap into its timed absence. Results suggest that in trace conditioning (Experiment 1), rats time for the absence of a stimulus by using its offset as a time marker. As in the standard gap procedure, the insertion of a reversed gap was expected to "stop" rats' internal clock. In contrast, a reversed gap of 1-, 5-, or 15-s duration "reset" the timing process in both trace conditioning (Experiment 2) and the reversed gap procedure (Experiment 3). A direct comparison of the standard and reversed gap procedures (Experiment 4) supported these findings. Results suggest that attentional mechanisms involving the salience or content of the gap might contribute to the response rule adopted in a gap procedure.

The across-fiber pattern theory and fuzzy logic: a matter of taste.

This article discusses a Fuzzy Logic (FL)-based model of neural coding and integration, proposed to be a formal extension of the Across-Fiber Pattern (AFP) theory. FL integration is conceptually similar to Bayesian reasoning, thus providing close-to-optimal decisions, and is also robust in that it does not require complete information. As a formal extension of AFP theory, the FL model describes sensory integration given multiple sources of information. When applied to gustation, the FL model is suggested to describe integration of information at the level of real-time pattern of single neural responses, population coding, and taste perception, as well as to provide a suitable description of taste mixtures.

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.

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.

Psychopharmacology of latent inhibition: a neural network approach.

A neural network model of classical conditioning is applied to the description of some aspects of the psychopharmacology of latent inhibition (LI). 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. In the framework of the model, it is assumed that indirect dopaminergic (DA) agonists (e.g. amphetamine and nicotine) increase, and DA receptor antagonists (e.g. haloperidol and alpha-flupenthixol) decrease, the effect of Novelty on attention. Computer simulations demonstrate that, under these assumptions, the model correctly describes: (1) the impairment of LI by amphetamine when a strong unconditioned stimulus (US) is used, (2) the impairment of LI by amphetamine when a nonsalient CS is used, (3) the impairment of LI by amphetamine administration when a short CS is used, (4) the facilitation of LI by alpha-flupenthixol when a weak US is used, (5) the facilitation of LI by haloperidol when a nonsalient CS is used, (6) the facilitation of LI by haloperidol with a strong US, and (7) the facilitation of LI by haloperidol with extended conditioning.

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.

Spatial and temporal cognitive mapping: a neural network approach.

Tolman suggested that cognitive behavior is purposive and can be described in terms of how differant goals are pursued. When pursuing these goals, animals and humans display a remarkable adaptability, which is the result of the combination of a goal-seeking mechanism and a cognitive map. Whereas the goal-seeking mechanism permits the animal to seek different goals, adopting alternative behavioral strategies that are independent of any set of responses, the cognitive map allows the integration of multiple independent pieces of knowledge. Although the concept of cognitive mapping has been mostly applied to spatial mapping, we describe how both spatial and temporal cognitive maps can be mechanistically implemented in terms of recurrent associative networks which store either the adjacency of spatial locations or the contiguity of temporal events. The reinjected predictions of spatial locations or temporal events in the network can be conceptualized as images and their sequences conceptualized as the process of imagining. The combination of goal-seeking systems and cognitive maps permits the description of problem solving tasks in terms of the sequence of subgoals (a plan) to be pursued to reach the goal. Whereas the hippocampus might play a major role in the storage of both spatial and temporal cognitive maps in association cortex, the frontal cortex might participate in goal-seeking tasks, decision making and planing.

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.