[Show abstract][Hide abstract] ABSTRACT: Experimentally naive mice matched the proportions of their temporal investments (visit durations) in two feeding hoppers to the proportions of the food income (pellets per unit session time) derived from them in three experiments that varied the coupling between the behavioral investment and food income, from no coupling to strict coupling. Matching was observed from the outset; it did not improve with training. When the numbers of pellets received were proportional to time invested, investment was unstable, swinging abruptly from sustained, almost complete investment in one hopper, to sustained, almost complete investment in the other-in the absence of appropriate local fluctuations in returns (pellets obtained per time invested). The abruptness of the swings strongly constrains possible models. We suggest that matching reflects an innate (unconditioned) program that matches the ratio of expected visit durations to the ratio between the current estimates of expected incomes. A model that processes the income stream looking for changes in the income and generates discontinuous income estimates when a change is detected is shown to account for salient features of the data.
Journal of the Experimental Analysis of Behavior 04/2007; 87(2):161-99. · 1.07 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Evidence suggests that the online combination of non-verbal magnitudes (durations, numerosities) is central to learning in both human and non-human animals [Gallistel, C.R., 1990. The Organization of Learning. MIT Press, Cambridge, MA]. The molecular basis of these computations, however, is an open question at this point. The current study provides the first direct test of temporal subtraction in a species in which the genetic code is available. In two experiments, mice were run in an adaptation of Gibbon and Church's [Gibbon, J., Church, R.M., 1981. Time left: linear versus logarithmic subjective time. J. Exp. Anal. Behav. 7, 87-107] time left paradigm in order to characterize typical responding in this task. Both experiments suggest that mice engaged in online subtraction of temporal values, although the generalization of a learned response rule to novel stimulus values resulted in slightly less systematic responding. Potential explanations for this pattern of results are discussed.
[Show abstract][Hide abstract] ABSTRACT: Neural network models of timing have struggled to account for animal timing capabilities using the accepted connectionist
assumptions, in most cases without postulating the existence of explicit neuronal time-keeping mechanisms. Current ethological
and physiological data, however, suggest that cellular oscillators form the foundation for animals’ temporal capacities. We
propose that these oscillators could be used as temporal filters that capture the temporal structure of the animal’s experience.
A model is presented that accounts for a number of the salient features of the feeding anticipatory response with only a single
circadian filter. This model goes beyond current entrainment models in that it correctly predicts the relationship between
the feeding period and the anticipatory interval. An alternative approach using multiple filters is examined that can account
for animals’ ability to correctly anticipate two daily feeding times.
Behavior Research Methods 01/1996; 28(2):217-223. · 2.12 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Preliminary review / Publisher’s description: Memory and the Computational Brain offers a provocative argument that goes to the heart of neuroscience, proposing that the field can and should benefit from the recent advances of cognitive science and the development of information theory over the course of the last several decades. * A provocative argument that impacts across the fields of linguistics, cognitive science, and neuroscience, suggesting new perspectives on learning mechanisms in the brain * Proposes that the field of neuroscience can and should benefit from the recent advances of cognitive science and the development of information theory * Suggests that the architecture of the brain is structured precisely for learning and for memory, and integrates the concept of an addressable read/write memory mechanism into the foundations of neuroscience * Based on lectures in the prestigious Blackwell-Maryland Lectures in Language and Cognition, and now significantly reworked and expanded to make it ideal for students and faculty.