Correction of response error versus stimulus error in the extinction of discriminated operant learning

Inhibition in discriminated operant learning: Tests of response-specificity after feature-negative and extinction learning

Six experiments with rats examined the nature of inhibition learned in an operant feature-negative (FN) discrimination. The results of prior experiments that examined instrumental extinction rather than FN learning suggest that inhibition can be very specific to the inhibited response. In Experiment 1, we trained lever-press and chain-pull responses in separate but parallel FN discriminations (AR1+, ABR1-, CR2+, and CDR2-) and then tested both inhibitors (B and D) with both responses. Of primary interest was the extent to which the inhibitors suppressed the response they were trained with (same-response inhibition) versus the other response (cross-response inhibition). We found that cross-response inhibition was robust and essentially equal to same-response inhibition. Experiment 2 replicated this result and confirmed stronger inhibition after FN learning than after a differential inhibition procedure (AR1+, BR1-, CR2+, and DR2-). There was also little evidence that cross-response inhibition was due to a demonstrable competing response. Experiment 3 found that cross-response inhibition did not depend on having the two responses reinforced by a common outcome. Experiments 4 and 5 then found that cross-response inhibition depended substantially (though not completely) on the transfer target response having been trained in its own FN discrimination. However, Experiment 6 found that inhibition after instrumental extinction (as opposed to FN learning) was still highly response-specific when the transferred-to response had been trained in an FN discrimination. The overall results suggest that the characteristics of inhibition in instrumental extinction and FN learning differ and that transfer of FN inhibition across responses depends at least partly on previous "inhibitability" of the target response. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The nervous system as a solution for implementing closed negative feedback control loops

Behavior can be regarded as the output of a system (action), as a function linking stimulus to response (reaction), or as an abstraction of the bidirectional relationship between the environment and the organism (interaction). When considering the latter possibility, a relevant question arises concerning how an organism can materially and continuously implement such a relationship during its lifetime in order to perpetuate itself. The feedback control approach has taken up the task of answering just that question. During the last several decades, said approach has been progressing and has started to be recognized as a paradigm shift, superseding certain canonical notions in mainstream behavior analysis, cognitive psychology, and even neuroscience. In this paper, we describe the main features of feedback control theory and its associated techniques, concentrating on its critiques of behavior analysis, as well as the commonalities they share. While some of feedback control theory's major critiques of behavior analysis arise from the fact that they focus on different levels of organization, we believe that some are legitimate and meaningful. Moreover, feedback control theory seems to blend with neurobiology more smoothly as compared to canonical behavior analysis, which only subsists in a scattered handful of fields. If this paradigm shift truly takes place, behavior analysts-whether they accept or reject this new currency-should be mindful of the basics of the feedback control approach.

The Role of the Lateral Habenula in Inhibitory Learning from Reward Omission

The lateral habenula (LHb) is a phylogenetically primitive brain structure that plays a key role in learning to inhibit distinct responses to specific stimuli. This structure is activated by primary aversive stimuli, cues predicting an imminent aversive event, unexpected reward omissions, and cues associated with the omission of an expected reward. The most widely described physiological effect of LHb activation is acutely suppressing midbrain dopaminergic signaling. However, recent studies have identified multiple means by which the LHb promotes this effect as well as other mechanisms of action. These findings reveal the complex nature of LHb circuitry. The present paper reviews the role of this structure in learning from reward omission. We approach this topic from the perspective of computational models of behavioral change that account for inhibitory learning to frame key findings. Such findings are drawn from recent behavioral neuroscience studies that use novel brain imaging, stimulation, ablation, and reversible inactivation techniques. Further research and conceptual work are needed to clarify the nature of the mechanisms related to updating motivated behavior in which the LHb is involved. As yet, there is little understanding of whether such mechanisms are parallel or complementary to the well-known modulatory function of the more recently evolved prefrontal cortex.

BEHAVIORAL AND NEUROBIOLOGICAL MECHANISMS OF PAVLOVIAN AND INSTRUMENTAL EXTINCTION LEARNING

This article reviews the behavioral neuroscience of extinction, the phenomenon in which a behavior that has been acquired through Pavlovian or instrumental (operant) learning decreases in strength when the outcome that reinforced it is removed. Behavioral research indicates that neither Pavlovian nor operant extinction depends substantially on erasure of the original learning but instead depends on new inhibitory learning that is primarily expressed in the context in which it is learned, as exemplified by the renewal effect. Although the nature of the inhibition may differ in Pavlovian and operant extinction, in either case the decline in responding may depend on both generalization decrement and the correction of prediction error. At the neural level, Pavlovian extinction requires a tripartite neural circuit involving the amygdala, prefrontal cortex, and hippocampus. Synaptic plasticity in the amygdala is essential for extinction learning, and prefrontal cortical inhibition of amygdala neurons encoding fear memories is involved in extinction retrieval. Hippocampal-prefrontal circuits mediate fear relapse phenomena, including renewal. Instrumental extinction involves distinct ensembles in corticostriatal, striatopallidal, and striatohypothalamic circuits as well as their thalamic returns for inhibitory (extinction) and excitatory (renewal and other relapse phenomena) control over operant responding. The field has made significant progress in recent decades, although a fully integrated biobehavioral understanding still awaits.