Spontaneous integration of temporal information: implications for representational/computational capacity of animals

Abstract

How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.

Behavior Stability and Individual Differences in Pavlovian Extended Conditioning

“…Some subjects do show something that could be described as an abrupt acquisition, but response variability is too large throughout the experiment to make this conclusion meaningful when, to put it simply, a sharp initial rise in response is yet another random fluctuation around the ideal average curve (see Figures S4, S6). Precisely for the same reason, although it is true that traditional associative models do not predict abrupt chances in behavior, our findings do not support representational or model-based models either (Gür et al, 2018). Response variability is so fine grained that its random, nowheredifferentiable nature is, in our opinion, unquestionable.…”

“…• The main average effects of overtraining are an extremely slow decrease of the post-CS response and a fast extinction (see Figure S10). Fast extinction points out that the response of the animals during the experiment was not driven by habit, contrary to what one might expect in long training histories (Gür et al, 2018).…”

Number and time in acquisition, extinction and recovery

“…Subjects in associative learning experiments make a temporal map of the conditioning experience (Balsam & Gallistel, 2009;Honig, 1981;Taylora, Joseph, Zhaoc, & Balsam, 2014). The temporal information in the map affects every aspect of Pavlovian and operantly conditioned behavior (Arcediano & Miller, 2002;Barnet, Grahame, & Miller, 1993;Barnet & Miller, 1996;Blaisdell, Denniston, & Miller, 1998;Burger, Denniston, & Miller, 2001;Cole, Barnet, & Miller, 1995;Cunningham & Shahan, 2018;Denniston, Blaisdell, & Miller, 1998, 2004Gallistel, Craig, & Shahan, 2019;Gür, Duyan, & Balci, 2017;Shahan & Cunningham, 2015;Theunissen & Miller, 1995;Thrailkill & Shahan, 2014).…”

“…Subjects appear to do computations with the wait times they have learned (Gür et al, 2017): For example, the rate of learning [1/(trials to acquisition)] is a scalar function of the C/T ratio, which, as already noted, is the ratio of the basal average wait time for reinforcement in the training context (C) and the average wait time (T) for reinforcement following the onset of the conditioned stimulus (CS for short). The larger the C/T ratio is, the fewer the number of reinforced trials required for the appearance of a conditioned response to the CS (Gallistel & Gibbon, 2000;Gibbon & Balsam, 1981;Gottlieb, 2008;Jenkins, Barnes, & Barrera, 1981;Sunsay & Bouton, 2008).…”

Probabilistic Information Modulates the Timed Response Inhibition Deficit in Aging Mice

“…Our earlier work has shown that humans and mice can integrate probability information into their temporal decisions in an adaptive fashion (e.g., maximizing reward-rate; Balci et al, 2009b; Kheifets and Gallistel, 2012; Çoskun et al, 2015; Akdoğan and Balcı, 2016) and they can do this abruptly and spontaneously (Tosun et al, 2016; for a review, see Gür et al, 2018). Regarding these functional endpoints, earlier studies show that sensitivity to probabilistic information is higher in young compared to elderly (Howard et al, 2008), which becomes more pronounced with extended practice (Simon et al, 2010).…”