How do animals represent space, time, number and rate? From insects to humans, Charles Gallistel explores the sophisticated computations performed in these ubiquitous yet neglected domains of animal learning. He proposes new and imaginative hypotheses about brain and mental processes and provides original insights about animal behavior using a computational-representational framework that is an exciting alternative to traditional associative theories of learning.Gallistel argues compellingly that experimental psychologists should begin to view the phenomena of learning within a framework that utilizes as the proper unit of analysis the computation and storage of a quantity, rather than the formation of an association that has been the basis of traditional learning theory. His approach reveals the formal structure of the environmental relationships that animals master to time and orient their behavior. It clarifies what representations different animals can and cannot compute and the nature of the computations by which animals derive these representations.The author backs up this thesis with studies that encompass a vast range of animal learning: animal navigation (the use of dead reckoning and cognitive maps); the mechanisms of timekeeping in the nervous system; the registration and utilization of time of occurrence (circadian phase) in learned behavior; the learning and use of temporal intervals and of numerosity; the computation of rates of occurrence; modern findings and theories of classical conditioning.