Feature-positive discriminations during a spatial-search task with humans

Pavlovian occasion setting in human fear and appetitive conditioning: Effects of trait anxiety and trait depression

Contexts and discrete stimuli often hierarchically influence the association between a stimulus and outcome. This phenomenon, called occasion setting, is central to modulation-based Pavlovian learning. We conducted two experiments with humans in fear and appetitive conditioning paradigms, training stimuli in differential conditioning, feature-positive discriminations, and feature-negative discriminations. We also investigated the effects of trait anxiety and trait depression on these forms of learning. Results from both experiments showed that participants were able to successfully learn which stimuli predicted the electric shock and monetary reward outcomes. Additionally, as hypothesized, the stimuli trained as occasion setters had little-to-no effect on simple reinforced or non-reinforced stimuli, suggesting the former were indeed occasion setters. Lastly, in fear conditioning, trait anxiety was associated with increases in fear of occasion setter/conditional stimulus compounds; in appetitive conditioning, trait depression was associated with lower expectations of monetary reward for the trained negative occasion setting compound and transfer of the negative occasion setter to the simple reinforced stimulus. These results suggest that clinically anxious individuals may have enhanced fear of occasion setting compounds, and clinically depressed individuals may expect less reward with compounds involving the negative occasion setter.

Occasion setting

Occasion setting refers to the ability of 1 stimulus, an occasion setter, to modulate the efficacy of the association between another, conditioned stimulus (CS) and an unconditioned stimulus (US) or reinforcer. Occasion setters and simple CSs are readily distinguished. For example, occasion setters are relatively immune to extinction and counterconditioning, and their combination and transfer functions differ substantially from those of simple CSs. Similarly, the acquisition of occasion setting is favored when stimuli are separated by longer intervals, by empty trace intervals, and are of different modalities, whereas the opposite conditions typically favor the acquisition of simple associations. Furthermore, the simple conditioning and occasion setting properties of a single stimulus can be independent, for example, that stimulus may simultaneously predict the occurrence of a reinforcer and indicate that another stimulus will not be reinforced. Many behavioral phenomena that are intractable to simple associative analysis are better understood within an occasion setting framework. Besides capturing the distinction between direct and modulatory control common to many arenas in neuroscience, occasion setting provides a model for the hierarchical organization of memory for events and event relations, and for contextual control more broadly. Although early lesion studies further differentiated between occasion setting and simple conditioning functions, little is known about the neurobiology of occasion setting. Modern techniques for precise manipulation and monitoring of neuronal activity in multiple brain regions are ideally suited for disentangling contributions of simple conditioning and occasion setting in associative learning. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The influence of landmark stability on control by occasion setters

In an operant serial feature-positive procedure, an occasion setter (OS_X) signals that a response will be reinforced in the presence of a second stimulus (e.g., a discriminative stimulus, A). During a transfer test, the OS is paired with a different discriminative stimulus. Experiment 1a tested transfer effects in a touchscreen-based spatial occasion setting task with pigeons. During training, four OSs (OS_W, OS_X, OS_Y, and OS_Z) were paired on separate trials with landmark A (LM_A) or B (LM_B) and the opportunity for a reinforced response at one location to the immediate left (R₁) or right (R₂) of the LM (OS_W→LM_A:R₁, OS_X→LM_A:R₂, OS_Y→LM_B:R₁, OS_Z→LM_B:R₂). Training also included non-reinforced trials of LM_A and LM_B alone (LM_A- and LM_B-) and trials of a non-modulated LM with R₁ and R₂ reinforced across separate trials (LM_C:R₁ and LM_C:R₂). After training, the number and spatial location of responses during test trials of a LM paired with the same OS as in training did not differ reliably from transfer tests of an OS paired with a different, modulated LM (OS_W→LM_B and OS_Y→LM_A), but did differ from transfer to the non-modulated LM (OS_X→LM_C). Experiment 1b utilized the same pigeons and training with LM_B to test the degree to which the spatial stability of a LM influenced transfer. Retraining with LM_A was intended to establish it as a non-modulated, stable LM (LM_A:R₂). Subsequent tests with LM_A revealed reduced modulation by the formerly trained OS (OS_W), and complete disruption of modulation of spatial location during transfer with a different OS (OS_Y). These findings further our understanding of the conditions under which OSs may develop and transfer modulation.

Blocking between landmarks during 2-D (touchscreen) and 3-D (ARENA) search tasks with pigeons

Many studies investigating cue competition have focused on the blocking effect. We investigated the blocking effect with pigeons using a landmark-based spatial search task in both a touchscreen preparation (Exp. 1a) and an automated remote environmental navigation apparatus (Exp. 1b). In Phase 1, two landmarks (LMs: A and Z) appeared on separate trials as colored circles among a row of eight (touchscreen) or six (ARENA) identical response units. Subjects were rewarded for pecking at a target response unit to the right of LM A and to the left of an extraneous LM, Z. During the blocking trials in Phase 2, LM X was presented in compound with a second LM (A) that had been previously trained. On control trials, LM Y was presented in compound with LM B and a target in the same manner as in the trials of AX, except that neither landmark had previously been trained with the target. All subjects were then tested with separate trials of A, X, B, and Y. Testing revealed poor spatial control by X relative to A and Y. We report the first evidence for a spatial-blocking effect in pigeons and additional support for associative effects (e.g., blocking) occurring under similar conditions (e.g., training sessions, spatial relationships, etc.) in 3-D and 2-D search tasks.

Feature-positive discriminations during a spatial-search task with humans

During feature-positive operant discriminations, a conditional cue, X, signals whether responses made during a second stimulus, A, are reinforced. Few studies have examined how landmarks, which can be trained to control the spatial distribution of responses during search tasks, might operate under conditional control. We trained college students to search for a target hidden on a computer monitor. Participants learned that responses to a hidden target location signaled by a landmark (e.g., A) would be reinforced only if the landmark was preceded by a colored background display (e.g., X). In Experiment 1, participants received feature-positive training (+←YB/ XA→+/A-/B-) with the hidden target to the right of A and to left of B. Responding during nonreinforced transfer test trials (XB-/YA-) indicated conditional control by the colored background, and spatial accuracy indicated a greater weighting of spatial information provided by the landmark than by the conditional cue. In Experiments 2a and 2b, the location of the target relative to landmark A was conditional on the colored background (+←YA/ XA→+/ ZB→+/ +←C /A-/B-). At test, conditional control and a greater weighting for the landmark's spatial information were again found, but we also report evidence for spatial interference by the conditional stimulus. Overall, we found that hierarchical accounts best explain the observed differences in response magnitude, whereas spatial accuracy was best explained via spatial learning models that emphasize the reliability, stability, and proximity of landmarks to a target.