Search Results
Discriminative fear conditioning requires learning to dissociate between safety cues and cues that predict negative outcomes yet little is known about what processes contribute to discriminative fear learning. According to attentional models of time perception, processes that distract from timing result in temporal underestimation. If discriminative fear learning only requires learning what cues predict what outcomes, and threatening stimuli distract attention from timing, then better discriminative fear learning should predict greater temporal distortion on threat trials. Alternatively, if discriminative fear learning also reflects a more accurate perceptual experience of time in threatening contexts, discriminative fear learning scores would predict less temporal distortion on threat trials, as time is perceived more veridically. Healthy young adults completed discriminative fear conditioning in which they learned to associate one stimulus (CS+) with aversive electrical stimulation and another stimulus (CS−) with non-aversive tactile stimulation and then an ordinal-comparison timing task during which CSs were presented as task-irrelevant distractors. Consistent with predictions, we found an overall temporal underestimation bias on CS+ relative to CS− trials. Differential skin conductance responses to the CS+ versus the CS− during conditioning served as a physiological index of discriminative fear conditioning and this measure predicted the magnitude of the underestimation bias, such that individuals exhibiting greater discriminative fear conditioning showed less underestimation on CS+ versus CS− trials. These results are discussed with respect to the nature of discriminative fear learning and the relationship between temporal distortions and maladaptive threat processing in anxiety.
Abstract
The major tenets of beat-frequency/coincidence-detection models of reward-related timing are reviewed in light of recent behavioral and neurobiological findings. This includes the emphasis on a core timing network embedded in the motor system that is comprised of a corticothalamic-basal ganglia circuit. Therein, a central hub provides timing pulses (i.e., predictive signals) to the entire brain, including a set of distributed satellite regions in the cerebellum, cortex, amygdala, and hippocampus that are selectively engaged in timing in a manner that is more dependent upon the specific sensory, behavioral, and contextual requirements of the task. Oscillation/coincidence-detection models also emphasize the importance of a tuned ‘perception’ learning and memory system whereby target durations are detected by striatal networks of medium spiny neurons (MSNs) through the coincidental activation of different neural populations, typically utilizing patterns of oscillatory input from the cortex and thalamus or derivations thereof (e.g., population coding) as a time base. The measure of success of beat-frequency/coincidence-detection accounts, such as the Striatal Beat-Frequency model of reward-related timing (SBF), is their ability to accommodate new experimental findings while maintaining their original framework, thereby making testable experimental predictions concerning diagnosis and treatment of issues related to a variety of dopamine-dependent basal ganglia disorders, including Huntington’s and Parkinson’s disease.
Abstract
One of the major challenges for computational models of timing and time perception is to identify a neurobiological plausible implementation that predicts various behavioral properties, including the scalar property and retrospective timing. The available timing models primarily focus on the scalar property and prospective timing, while virtually ignoring the computational accessibility. Here, we first selectively review timing models based on ramping activity, oscillatory pattern, and time cells, and discuss potential challenges for the existing models. We then propose a multifrequency oscillatory model that offers computational accessibility, which could account for a much broader range of timing features, including both retrospective and prospective timing.
Basic mechanisms of interval timing and associative learning are shared by many animal species, and develop quickly in early life, particularly across infancy, and childhood. Indeed, John Wearden in his book “The Psychology of Time Perception”, which is based on decades of his own research with colleagues, and which our commentary serves to primarily review, has been instrumental in implementing animal models and methods in children and adults, and has revealed important similarities (and differences) between human timing (and that of animals) when considered within the context of scalar timing theory. These seminal studies provide a firm foundation upon which the contemporary multifaceted field of timing and time perception has since advanced. The contents of the book are arguably one piece of a larger puzzle, and as Wearden cautions, “The reader is warned that my own contribution to the field has been exaggerated here, but if you are not interested in your own work, why would anyone else be?” Surely there will be many interested readers, however the book is noticeably lacking in it neurobiological perspective. The mind (however it is conceived) needs a brain (even if behaviorists tend to say “the brain behaves”, and most neuroscientists currently have a tenuous grasp on the neural mechanisms of temporal cognition), and to truly understand the psychology of time, brain and behavior must go hand in hand regardless of the twists, turns, and detours along the way.
Although fear-producing treatments (e.g., electric shock) and pleasure-inducing treatments (e.g., methamphetamine) have different emotional valences, they both produce physiological arousal and lead to effects on timing and time perception that have been interpreted as reflecting an increase in speed of an internal clock. In this commentary, we review the results reported by Fayolle et al. (2015): Behav. Process., 120, 135–140) and Meck (1983: J. Exp. Psychol. Anim. Behav. Process., 9, 171–201) using electric shock and by Maricq et al. (1981: J. Exp. Psychol. Anim. Behav. Process., 7, 18–30) using methamphetamine in a duration-bisection procedure across multiple duration ranges. The psychometric functions obtained from this procedure relate the proportion ‘long’ responses to signal durations spaced between a pair of ‘short’ and ‘long’ anchor durations. Horizontal shifts in these functions can be described in terms of attention or arousal processes depending upon whether they are a fixed number of seconds independent of the timed durations (additive) or proportional to the durations being timed (multiplicative). Multiplicative effects are thought to result from a change in clock speed that is regulated by dopamine activity in the medial prefrontal cortex. These dopaminergic effects are discussed within the context of the striatal beat frequency model of interval timing (Matell & Meck, 2004: Cogn. Brain Res., 21, 139–170) and clinical implications for the effects of emotional reactivity on temporal cognition (Parker et al., 2013: Front. Integr. Neurosci., 7, 75).
Interval timing behavior and its sensitivity to both temporal context and changes in dopamine (DA) levels has recently received considerable attention. Nevertheless, the exact manner in which those interactions occur is far from clear. We examined temporal reproduction with feedback in the supra-seconds range as a function of DA levels using two well-studied timing procedures. Healthy young and aged participants were studied as well as Parkinson’s disease (PD) patients tested ON and OFF their dopaminergic medication. The findings confirm the hypothesis that the ‘migration effect’ (e.g., ‘short’ durations are over-produced and ‘long’ durations are under-produced) in PD patients and the closely related Vierordt’s effect are largely influenced by the effective level of DA and in the case of the ‘migration effect’ by the probability of feedback as well. Using a Bayesian model seeking optimal timing under conditions of uncertainty, we were able to accurately simulate the distorted patterns of temporal reproduction in all groups of participants. As DA levels decrease across groups, optimal timing behavior shifts towards a greater reliance on a statistical representation of all of the durations reproduced within a specific temporal context rather than on the representation of a single duration being timed on any one trial. This analysis demonstrates the utility of Bayesian models of interval timing and highlights the importance of DA levels on clock speed and the associated uncertainty that contributes to temporal distortions.