Behavioral studies of spinal conditioning: The spinal cord is smarter than you think it is.

Abstract

In 1988 Robert Rescorla published an article in the Annual Review of Neuroscience that addressed the circumstances under which learning occurs, some key methodological issues, and what constitutes an example of learning. The article has inspired a generation of neuroscientists, opening the door to a wider range of learning phenomena. After reviewing the historical context for his article, its key points are briefly reviewed. The perspective outlined enabled the study of learning in simpler preparations, such as the spinal cord. The period after 1988 revealed that pain (nociceptive) stimuli can induce a lasting sensitization of spinal cord circuits, laying down a kind of memory mediated by signal pathways analogous to those implicated in brain dependent learning and memory. Evidence suggests that the spinal cord is sensitive to instrumental response-outcome (R-O) relations, that learning can induce a peripheral modification (muscle memory) that helps maintain the learned response, and that learning can promote adaptive plasticity (a form of metaplasticity). Conversely, exposure to uncontrollable stimulation disables the capacity to learn. Spinal cord neurons can also abstract that stimuli occur in a regular (predictable) manner, a capacity that appears linked to a neural oscillator (central pattern generator). Disrupting communication with the brain has been shown to transform how GABA affects neuronal function (an example of ionic plasticity), releasing a brake that enables plasticity. We conclude by presenting a framework for understanding these findings and the implications for the broader study of learning.

Ionic Plasticity: Common Mechanistic Underpinnings of Pathology in Spinal Cord Injury and the Brain

“…It is assumed that this process, ionic plasticity, normally subserves an adaptive function, removing a GABA-dependent brake on neural activity to promote plasticity in a particular neural circuit. From this perspective, ionic plasticity is required for learning [ 170 ]. Indeed, bumetanide has been shown to disrupt the development of hippocampal LTP in vitro and inhibitory avoidance learning in vivo [ 171 ].…”

“…Further increases in excitability could saturate NMDA-Receptor mediated plasticity and undermine learning about specific relations ( Figure 3 D). Given these observations, we have suggested that GABA-dependent inhibition limits the scope of neural activity whereas the removal of this brake broadens the response profile [ 170 ]. Likewise, others have proposed that compromised inhibition reduces the fidelity of information transfer, leading to a loss of pathway-specific LTP [ 26 , 172 ].…”

“…Treatments that target ionic plasticity should have a more selective effect, to re-establish GABAergic inhibition in neural regions where intracellular Cl − concentrations are high while having little effect on other parts of the CNS. The one caveat concerns the presumed role of ionic plasticity in adaptive learning [ 170 ]. To the extent that a lessening of GABAergic inhibition is required for learning, treatments that generally lower intracellular Cl − concentrations may impair this process.…”

Developments in associative theory: A tribute to the contributions of Robert A. Rescorla.

“…In Nairne and Rescorla’s (1981) work on second-order conditioning described in the previous section, they demonstrated that even though first-order auditory CSs did not evoke key pecking in autoshaping, second-order CSs that predicted auditory CS reinforcers came to evoke pecking, showing that the association between the auditory CS and the US was there, but not evident in the pecking behavior that is typically measured in that task. In reviewing work on learning in the spinal cord, Grau et al (2022) point out that Rescorla noted that one function of conditioning might be to promote biologically preexisting response patterns specific to a CS, but this learning is still subject to the same general principles of learning. Together, work showing that the CS may determine the form of the CR showed quite clearly that the inferences that we might make about learning depend on what we are measuring during a CS and whether the response we are measuring is compatible with the qualitative features of that CS.…”

“…Although Bob spent most of his research energy addressing the first two questions, he also emphasized the importance of “the performance problem,” and there are clear instances with respect to all three of these questions where his work was ground-breaking. This organizational structure has been adopted by former students and collaborators over the years and still provides a very clear framework for understanding basic learning processes (e.g., Colwill, 2019; Delamater & Lattal, 2014; Grau et al, 2022; Lattal, 2013). The rest of this paper will explore in more detail some of Bob’s key contributions within each of these, sometimes overlapping, domains.…”